diff --git a/sangraha/tok_sangraha/split/finalaa_splitac b/sangraha/tok_sangraha/split/finalaa_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..84740256feb9c182815c0bc4a1c7cfd9ee176c97
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalaa_splitac
@@ -0,0 +1 @@
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\u0932\u093f\u090f \u0926\u0941\u0915\u093e\u0928\u094b\u0902 \u092e\u0947\u0902 \u0932\u093e\u0916\u094b\u0902 \u0930\u0941\u092a\u090f \u0915\u093e \u0938\u093e\u092e\u093e\u0928 \u092d\u0930\u093e \u0925\u093e,\u092a\u0930\u0902\u0924\u0941 \u092e\u0902\u0926\u0940 \u0915\u0940 \u092e\u093e\u0930 \u0915\u0947 \u091a\u0932\u0924\u0947 \u0907\u0938 \u092c\u093e\u0930 \u0909\u0928\u094d\u0939\u0947\u0902 \u092e\u093e\u092f\u0942\u0938\u0940 \u0939\u0940 \u0939\u093e\u0925 \u0932\u0917\u0940 \u0939\u0948\u0964 \u0909\u0927\u0930, \u0907\u0938 \u092c\u093e\u0930 \u0915\u0930\u0935\u093e\u091a\u094c\u0925 \u092e\u0947\u0902 \u0938\u0924\u094d\u0924\u0930 \u0938\u093e\u0932 \u092c\u093e\u0926 \u092c\u0928\u0947 \u0936\u0941\u092d \u0938\u0902\u092f\u094b\u0917 \u0915\u0947 \u091a\u0932\u0924\u0947 \u0938\u0941\u0939\u093e\u0917\u093f\u0928\u094b\u0902 \u092e\u0947\u0902 \u0935\u093f\u0936\u0947\u0937 \u0909\u0924\u094d\u0938\u093e\u0939 \u0926\u0947\u0916\u093e \u0917\u092f\u093e 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diff --git a/sangraha/tok_sangraha/split/finalab_splitac b/sangraha/tok_sangraha/split/finalab_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..2c3d22bc08344996c9929f316c24ee73511ef9c5
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalab_splitac
@@ -0,0 +1 @@
+{"doc_id":"1af4d6cc7ba0cdfb0dd9d9871cae9decdbb5f06d","text":"Delhi Election Results : \u0926\u093f\u0932\u094d\u0932\u0940 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u091a\u0941\u0928\u093e\u0935\u094b\u0902 \u092e\u0947\u0902 \u0915\u094b\u0902\u0921\u0932\u0940 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0947 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0928\u0947 \u0936\u093e\u0928\u0926\u093e\u0930 \u091c\u0940\u0924 \u0926\u0930\u094d\u091c \u0915\u0940 \u0939\u0948\u0964 \u0935\u093f\u0930\u094b\u0927\u0940 \u092a\u094d\u0930\u0924\u094d\u092f\u093e\u0936\u093f\u092f\u094b\u0902 \u092a\u0930 \u0936\u0941\u0930\u0942 \u0938\u0947 \u092c\u0922\u093c\u0924 \u092c\u0928\u093e \u0930\u0916\u0940 \u0925\u0940\u0964\n Delhi Election Results : \u0926\u093f\u0932\u094d\u0932\u0940 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u091a\u0941\u0928\u093e\u0935 \u0915\u0947 \u0928\u0924\u0940\u091c\u0947 \u0918\u094b\u0937\u093f\u0924 \u0939\u094b \u0917\u090f \u0939\u0948\u0902\u0964 \u0926\u093f\u0932\u094d\u0932\u0940 \u0915\u0940 \u0915\u094b\u0902\u0921\u0932\u0940 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0940\u091f \u092a\u0930 \u0906\u092a \u092a\u094d\u0930\u0924\u094d\u092f\u093e\u0915\u094d\u0937\u0940 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0928\u0947 \u091c\u0940\u0924 \u0926\u0930\u094d\u091c \u0915\u0940 \u0939\u0948\u0964 \u0906\u092e \u0906\u0926\u092e\u0940 \u092a\u093e\u0930\u094d\u091f\u0940 \u0915\u0947 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0915\u0947 \u0938\u093e\u092e\u0928\u0947 \u092e\u0948\u0926\u093e\u0928 \u092e\u0947\u0902 \u092d\u093e\u0930\u0924\u0940\u092f \u091c\u0928\u0924\u093e \u092a\u093e\u0930\u094d\u091f\u0940 \u0915\u0947 \u0930\u093e\u091c \u0915\u0941\u092e\u093e\u0930 \u0925\u0947\u0964 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0928\u0947 \u0936\u0941\u0930\u0941\u0906\u0924 \u0938\u0947 \u092c\u0922\u093c\u0924 \u092c\u0928\u093e\u090f \u0939\u0941\u090f \u0925\u0940\u0964\n \u0926\u093f\u0932\u094d\u0932\u0940 \u0915\u0940 \u0915\u094b\u0902\u0921\u0932\u0940 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0940\u091f \u092a\u0930 \u0906\u092e \u0906\u0926\u092e\u0940 \u092a\u093e\u0930\u094d\u091f\u0940 (AAP) \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930, \u092d\u093e\u0930\u0924\u0940\u092f \u091c\u0928\u0924\u093e \u092a\u093e\u0930\u094d\u091f\u0940 (\u092c\u0940\u091c\u0947\u092a\u0940) \u0915\u0947 \u0930\u093e\u091c \u0915\u0941\u092e\u093e\u0930 \u0914\u0930 \u0915\u093e\u0902\u0917\u094d\u0930\u0947\u0938 \u0905\u092e\u0930\u0940\u0936 \u0938\u093f\u0902\u0939 \u0917\u094c\u0924\u092e \u0915\u0947 \u092c\u0940\u091a \u092e\u0941\u0915\u093e\u092c\u0932\u093e \u0925\u093e\u0964 \u0932\u0947\u0915\u093f\u0928 \u0906\u092e \u0906\u0926\u092e\u0940 \u092a\u093e\u0930\u094d\u091f\u0940 \u092a\u094d\u0930\u0924\u094d\u092f\u093e\u0936\u0940 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0928\u0947 \u092a\u0939\u0932\u0947 \u091a\u0930\u0923 \u0938\u0947 \u092c\u0922\u093c\u0924 \u092c\u0928\u093e\u0928\u093e \u0936\u0941\u0930\u0942 \u0915\u0930 \u0926\u093f\u092f\u093e\u0964 \u091c\u094b \u0915\u093f \u0905\u0902\u0924 \u0924\u0915 \u0915\u093e\u092f\u092e \u0930\u0939\u0940\u0964 \u0915\u0941\u0932\u0926\u0940\u092a \u0915\u0941\u092e\u093e\u0930 \u0928\u0947 \u092d\u093e\u091c\u092a\u093e \u092a\u094d\u0930\u0924\u094d\u092f\u093e\u0936\u0940 \u0930\u093e\u091c\u0915\u0941\u092e\u093e\u0930 \u0915\u094b \u092c\u0921\u093c\u0947 \u0905\u0902\u0924\u0930 \u0938\u0947 \u0939\u0930\u093e\u092f\u093e \u0939\u0948\u0964\n ","type":"web"}
diff --git a/sangraha/tok_sangraha/split/finalae_splitac b/sangraha/tok_sangraha/split/finalae_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..35f2643287922b7c7c74024925fb08df55f54f5f
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalae_splitac
@@ -0,0 +1 @@
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diff --git a/sangraha/tok_sangraha/split/finalaf_splitac b/sangraha/tok_sangraha/split/finalaf_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..286c9cc10a26fe9c861c93d994fb171b50c0af34
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalaf_splitac
@@ -0,0 +1 @@
+{"doc_id":"f70b61f298679182caf3bacf99e1e5eb8c1c1198","text":"\u092e\u094b\u091f\u0940 \u0927\u093e\u0917\u093e - \u091c\u0932\u094d\u0926\u0940 \u0914\u0930 \u0906\u0938\u093e\u0928\u0940 \u0938\u0947 \u092c\u0941\u0928\u093e\u0908 \u0915\u0947 \u0932\u093f\u090f \u0906\u0926\u0930\u094d\u0936\u0964 \u092f\u0939 \u0936\u0941\u0930\u0941\u0906\u0924\u0940 \u0915\u0947 \u0932\u093f\u090f \u090f\u0915\u0926\u092e \u0938\u0939\u0940 \u0939\u0948, \u0915\u0947 \u0930\u0942\u092a \u092e\u0947\u0902 \u092a\u0930\u093f\u0923\u093e\u092e \u0938\u092e\u092f \u0928\u0939\u0940\u0902 \u0932\u0917\u0947\u0917\u093e, \u0914\u0930 \u0906\u092a \u0924\u0941\u0930\u0902\u0924 \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0914\u0930 \u0938\u0939\u0940 \u0917\u0932\u0924\u093f\u092f\u094b\u0902 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0907\u0938\u0915\u0947 \u0905\u0932\u093e\u0935\u093e, \u092b\u0948\u0936\u0928 \u092e\u0947\u0902 \u0905\u092c \u092e\u094b\u091f\u0940 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\u091b\u0939 \u091f\u093e\u0902\u0915\u0947 \u0915\u093e \u090f\u0915 \u0936\u094d\u0930\u0943\u0902\u0916\u0932\u093e\u0964\n - \u0926\u0938\u094d\u0924\u093e\u0928\u0947 \u0915\u0947 \u0938\u093e\u0925 \u0915\u0947 \u0930\u0942\u092a \u092e\u0947\u0902, \u0939\u0941\u0915 \u092a\u0930 \u091a\u094c\u0925\u0947 \u092a\u093e\u0936 \u0905\u0902\u0924 \u0924\u0915 \u0938\u094d\u0924\u0902\u092d \u0905\u0928\u0941\u0938\u0942\u091a\u093f\u0924 \u091c\u093e\u0924\u093f \u092c\u0928\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u0914\u0930 \u0907\u0924\u0928\u0947 \u092a\u0930\u0964 \u0915\u0941\u0932 4 \u091a\u092e\u094d\u092e\u091a\u0964 \u090f\u0938 \/ \u090f\u0928\u0964\n - \u092c\u0938 \u090f\u0915 \u0914\u0930 13 \u092a\u0902\u0915\u094d\u0924\u093f\u092f\u094b\u0902 \u092c\u093e\u0901\u0927, \u0909\u0928\u092e\u0947\u0902 \u0938\u0947 \u092a\u094d\u0930\u0924\u094d\u092f\u0947\u0915 \u0915\u0947 \u0905\u0902\u0924 \u092e\u0947\u0902 \u0915\u093e\u092e 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\u090f\u0915 \u0906\u092f\u0924 \u0915\u0947 \u0938\u093e\u0925 \u0936\u0941\u0930\u0942 \u0939\u094b\u0924\u093e \u0939\u0948 \u0914\u0930 seamed \u0935\u093f\u0935\u0930\u0923 \u0915\u0940 \u0906\u0935\u0936\u094d\u092f\u0915\u0924\u093e \u0939\u0948\u0964\n \u092e\u094b\u091f\u0940 \u0927\u093e\u0917\u093e \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 \u0915\u093f\u092f\u093e \u0914\u0930 \u0939\u0941\u0915 \u0915\u0947 \u0906\u0915\u093e\u0930 12 \u092e\u093f\u092e\u0940\u0964\n \u0906\u0930\u0902\u092d \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u092a\u094d\u0930\u0915\u093e\u0930 23 \u091b\u094b\u0930\u094b\u0902\u0964 \u0907\u0938\u0915\u0947 \u0905\u0932\u093e\u0935\u093e, \u0915\u093e\u092e \u0915\u0940 \u092a\u0902\u0915\u094d\u0924\u093f\u092f\u094b\u0902 \u0915\u0947 \u0930\u0942\u092a \u092e\u0947\u0902 \u0928\u093f\u092e\u094d\u0928\u093e\u0928\u0941\u0938\u093e\u0930 \u0915\u093f\u092f\u093e \u091c\u093e\u0924\u093e \u0939\u0948\u0903\n- \u092c\u0938 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\u0930\u0915\u094d\u0937\u093e \u0915\u0930\u0947\u0917\u093e\u0964\n 54 \u0938\u0947\u092e\u0940 \u0915\u0947 \u0938\u093f\u0930 \u092a\u0930\u093f\u0927\u093f \u092a\u0930 \u0917\u0923\u0928\u093e, \u090f\u0915 \u091b\u094b\u091f\u0947 \u0938\u0947 \u0916\u0940\u0902\u091a\u0964 \u092a\u0930\u093f\u092a\u0924\u094d\u0930 \u092c\u0941\u0928\u093e\u0908 \u0906\u0915\u093e\u0930 10, \u0930\u0947\u0916\u093e 40 \u0938\u0947\u092e\u0940 \u092a\u0930 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u0928 \u0915\u093f\u092f\u093e\u0964\n \u092c\u0941\u0928\u093e\u0908 \u0915\u093e \u0918\u0928\u0924\u094d\u0935\u0903 9 \u091b\u094b\u0930\u094b\u0902 14 \u092a\u0902\u0915\u094d\u0924\u093f\u092f\u094b\u0902 * \u0917\u093e\u0930\u094d\u091f\u0930 \u0938\u093f\u0932\u093e\u0908 \u092e\u0947\u0902 = \u0913\u0930 10 \u0938\u0947\u092e\u0940 \u0915\u0947 \u0935\u0930\u094d\u0917\u0964\n \u0928\u094c\u0915\u0930\u0940 \u0915\u093e \u0935\u093f\u0935\u0930\u0923\u0903\n- \u0921\u093e\u092f\u0932 \u0939\u092e\u0947\u0936\u093e \u0915\u0940 \u0924\u0930\u0939 43 \u091b\u094b\u0930\u094b\u0902\u0964 \u0909\u0928\u094d\u0939\u0947\u0902 \u090f\u0915 \u0938\u0930\u094d\u0915\u0932 \u092e\u0947\u0902 \u092c\u0902\u0926 \u0915\u0930\u094b, \u092a\u093f\u091b\u0932\u0947 \u091f\u094b\u092a\u0940 \u092e\u0947\u0902 \u0915\u0947 \u0930\u0942\u092a \u092e\u0947\u0902\u0964\n - \u092a\u0902\u0915\u094d\u0924\u093f\u092f\u093e\u0901 1-6 \u0917\u093e\u0930\u094d\u091f\u0930 \u0938\u093f\u0932\u093e\u0908 \u092e\u0947\u0902 \u092c\u0928\u0947 \u0939\u094b\u0924\u0947 \u0939\u0948\u0902\u0903 \u091a\u0947\u0939\u0930\u0947 \u0914\u0930 \u0915\u0947 \u0930\u0948\u0902\u0915 backstitches \u0932\u0942\u092a \u092c\u093e\u0930\u0940-\u092c\u093e\u0930\u0940 \u0938\u0947\u0964\n - \u092a\u0902\u0915\u094d\u0924\u093f\u092f\u093e\u0901 7-13 \u092c\u0941\u0928\u093e \u0939\u0941\u0906 \u0938\u093e\u092e\u0928\u0947 \u0915\u0922\u093c\u093e\u0908\u0964\n - \u0918\u091f\u093e\u0935 \u0915\u0930\u094b \u0914\u0930 \u0907\u0938 \u091f\u094b\u092a\u0940 \u0915\u0947 \u0938\u093e\u0925 \u0939\u0940 \u092a\u093f\u091b\u0932\u0947 \u090f\u0915 \u0915\u094b \u092a\u0942\u0930\u093e\u0903 \u090f\u0915 \u0938\u093e\u0925 *, 5 * \u091a\u0947\u0939\u0930\u0947 \u090f\u0915 \u0926\u094b \u091b\u094b\u0930\u094b\u0902 \u0915\u0940 \u0936\u094d\u0930\u0943\u0902\u0916\u0932\u093e, * \u0915\u0930\u0928\u0947 \u0938\u0947 \u0926\u094b\u0939\u0930\u093e\u0928\u0947 *\u0964 \u092b\u093f\u0930 \u092c\u0939\u0941\u0924 \u0905\u0902\u0924 \u0924\u0915 \u0918\u091f\u093e\u0935 \u0915\u0947 \u092c\u0940\u091a \u091b\u094b\u0930\u094b\u0902 \u0915\u0940 \u0938\u0902\u0916\u094d\u092f\u093e \u0915\u094b \u0915\u092e, \u0914\u0930 \u0907\u0924\u0928\u0947 \u092a\u0930\u0964\n \u0905\u092a\u0928\u0940 \u0930\u091a\u0928\u093e\u0924\u094d\u092e\u0915\u0924\u093e \u0915\u093e \u0906\u0928\u0902\u0926 \u0932\u0947\u0902!\n ","type":"web"}
diff --git a/sangraha/tok_sangraha/split/finalag_splitac b/sangraha/tok_sangraha/split/finalag_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..ee3834b66b45c4d29af75e58bc3af8d11621e14c
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalag_splitac
@@ -0,0 +1 @@
+{"doc_id":"b7e359c682dede4d95d44476c21b307de2af1036","text":"\u0915\u0947\u0902\u0926\u094d\u0930 \u0936\u093e\u0938\u093f\u0924 \u092a\u094d\u0930\u0926\u0947\u0936 \u092e\u0947\u0902 \u092c\u093f\u091c\u0932\u0940 \u0909\u0924\u094d\u092a\u093e\u0926\u0928 \u0915\u094b \u0926\u094b\u0917\u0941\u0928\u093e \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u090f\u0928\u090f\u091a\u092a\u0940\u0938\u0940 \u0914\u0930 \u090f\u0915 \u0938\u0902\u092f\u0941\u0915\u094d\u0924 \u0909\u0926\u094d\u092f\u092e \u0926\u094d\u0935\u093e\u0930\u093e 6,272 \u092e\u0947\u0917\u093e\u0935\u0949\u091f \u0915\u094d\u0937\u092e\u0924\u093e \u0935\u093e\u0932\u0940 \u0915\u0941\u0932 \u0906\u0920 \u0928\u0908 \u092a\u0928\u092c\u093f\u091c\u0932\u0940 \u092c\u093f\u091c\u0932\u0940 \u092a\u0930\u093f\u092f\u094b\u091c\u0928\u093e\u0913\u0902 \u0915\u094b \u0906\u0917\u0947 \u092c\u0922\u093c\u093e\u092f\u093e \u091c\u093e \u0930\u0939\u093e \u0939\u0948\u0964\n \u0909\u0928\u094d\u0939\u094b\u0902\u0928\u0947 \u0915\u0939\u093e \u0915\u093f \u092a\u0928\u092c\u093f\u091c\u0932\u0940 \u092a\u0930\u093f\u092f\u094b\u091c\u0928\u093e\u0913\u0902 \u0915\u0947 \u0915\u094d\u0930\u093f\u092f\u093e\u0928\u094d\u0935\u092f\u0928 \u092e\u0947\u0902 \u0939\u094b \u0930\u0939\u0940 \u0926\u0947\u0930\u0940 \u0915\u094b \u0938\u092e\u093e\u092a\u094d\u0924 \u0915\u0930 \u0926\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948 \u0914\u0930 \u0928\u093f\u0937\u094d\u092a\u093e\u0926\u0928 \u0915\u0940 \u0917\u0924\u093f \u0915\u094b \u0924\u0947\u091c \u0915\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u0907\u0938\u0915\u0947 \u0938\u093e\u0925 \u0939\u0940 \u092e\u094c\u091c\u0942\u0926\u093e \u092c\u093f\u091c\u0932\u0940 \u0915\u092e\u0940 \u0915\u094b \u0926\u0942\u0930 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u092c\u0921\u093c\u0947 \u092a\u0948\u092e\u093e\u0928\u0947 \u092a\u0930 \u0915\u094d\u0937\u092e\u0924\u093e \u0935\u093f\u0938\u094d\u0924\u093e\u0930 \u0915\u093e\u0930\u094d\u092f\u0915\u094d\u0930\u092e \u0936\u0941\u0930\u0942 \u0915\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964\n \u0905\u0927\u093f\u0915\u093e\u0930\u093f\u092f\u094b\u0902 \u0928\u0947 \u0915\u0939\u093e \u0915\u093f 6,272 \u092e\u0947\u0917\u093e\u0935\u0949\u091f \u0909\u0924\u094d\u092a\u093e\u0926\u0928 \u0915\u094d\u0937\u092e\u0924\u093e \u0935\u093e\u0932\u0940 \u0906\u0920 \u092c\u093f\u091c\u0932\u0940 \u092a\u0930\u093f\u092f\u094b\u091c\u0928\u093e\u0913\u0902 \u0915\u094b \u0915\u094d\u0930\u093f\u092f\u093e\u0928\u094d\u0935\u092f\u0928 \u0915\u0947 \u0932\u093f\u090f \u0932\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u0907\u0928\u092e\u0947\u0902 \u0938\u0947 4,108 \u092e\u0947\u0917\u093e\u0935\u0949\u091f \u0915\u0940 \u0915\u0941\u0932 \u0915\u094d\u0937\u092e\u0924\u093e \u0935\u093e\u0932\u0940 \u092a\u093e\u0902\u091a \u092a\u0930\u093f\u092f\u094b\u091c\u0928\u093e\u0913\u0902 \u0915\u094b \u090f\u0928\u090f\u091a\u092a\u0940\u0938\u0940 \u0926\u094d\u0935\u093e\u0930\u093e \u0914\u0930 \u0924\u0940\u0928 \u0905\u0928\u094d\u092f \u0915\u094b \u091c\u092e\u094d\u092e\u0942-\u0915\u0936\u094d\u092e\u0940\u0930 \u0938\u0930\u0915\u093e\u0930 \u0915\u0947 \u0938\u093e\u0925 \u0938\u0902\u092f\u0941\u0915\u094d\u0924 \u0909\u0926\u094d\u092f\u092e \u0915\u0947 \u091c\u0930\u093f\u092f\u0947 \u0915\u094d\u0930\u093f\u092f\u093e\u0928\u094d\u0935\u093f\u0924 \u0915\u093f\u092f\u093e \u091c\u093e\u090f\u0917\u093e\u0964\n \u0938\u0902\u0918 \u0936\u093e\u0938\u093f\u0924 \u092a\u094d\u0930\u0926\u0947\u0936 \u0915\u0940 \u0905\u0928\u0941\u092e\u093e\u0928\u093f\u0924 \u092a\u0928\u092c\u093f\u091c\u0932\u0940 \u0915\u094d\u0937\u092e\u0924\u093e 20,000 \u092e\u0947\u0917\u093e\u0935\u0949\u091f \u0939\u0948, \u091c\u093f\u0938\u092e\u0947\u0902 \u0938\u0947 \u0932\u0917\u092d\u0917 16,475 \u092e\u0947\u0917\u093e\u0935\u0949\u091f \u0915\u094d\u0937\u092e\u0924\u093e \u0915\u094b \u091a\u093f\u0939\u094d\u0928\u093f\u0924 \u0915\u093f\u092f\u093e \u091c\u093e \u091a\u0941\u0915\u093e \u0939\u0948\u0964\n ","type":"web"}
diff --git a/sangraha/tok_sangraha/split/finalah_splitac b/sangraha/tok_sangraha/split/finalah_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..44cdc82115b067179a9d390f58ea960731d57880
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalah_splitac
@@ -0,0 +1 @@
+{"doc_id":"3e2720dc0e4a7b776e171c9f36475d8c27ca33d5bda00e11d690c05a531c6670","text":"Jagdishpur Vidhan Sabha constituency: \u091c\u0917\u0926\u0940\u0936\u092a\u0941\u0930 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0940\u091f \u092a\u0930 \u0938\u092c\u0938\u0947 \u0905\u0939\u092e \u092d\u0942\u092e\u093f\u0915\u093e \u092e\u0947\u0902 \u092f\u093e\u0926\u0935 \u0914\u0930 \u0930\u093e\u091c\u092a\u0942\u0924 \u0939\u0948\u0902. 2010 \u092e\u0947\u0902 \u092f\u0939\u093e\u0902 54.3 \u092a\u094d\u0930\u0924\u093f\u0936\u0924 \u0935\u094b\u091f\u093f\u0902\u0917 \u0939\u0941\u0908 \u0925\u0940.\n\u092c\u093f\u0939\u093e\u0930 \u090f\u0915 \u092c\u093e\u0930 \u092b\u093f\u0930 \u0905\u092a\u0928\u093e \u092e\u0941\u0916\u094d\u092f\u092e\u0902\u0924\u094d\u0930\u0940 \u091a\u0941\u0928\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0924\u0948\u092f\u093e\u0930 \u0939\u0948. \u092d\u094b\u091c\u092a\u0941\u0930 \u091c\u093f\u0932\u0947 \u0915\u0940 \u0938\u092c\u0938\u0947 \u091a\u0930\u094d\u091a\u093f\u0924 \u0914\u0930 \u0939\u0949\u091f \u0938\u0940\u091f \u091c\u0917\u0926\u0940\u0936\u092a\u0941\u0930 (Jagdishpur Vidhan Sabha) \u0938\u0947 \u091c\u0947\u0921\u0940\u092f\u0942 (JDU) \u0928\u0947 \u0926\u093e\u0935\u093e \u092a\u0902\u091a\u093e\u092f\u0924 \u0915\u0940 \u091a\u0930\u094d\u091a\u093f\u0924 \u092e\u0941\u0916\u093f\u092f\u093e \u0936\u0941\u0937\u094d\u092e\u0932\u0924\u093e \u092a\u0930 \u092d\u0930\u094b\u0938\u093e \u0915\u0930 \u0909\u0928\u0915\u094b \u091a\u0941\u0928\u093e\u0935\u0940 \u092e\u0948\u0926\u093e\u0928 \u092e\u0947\u0902 \u0909\u0924\u093e\u0930\u093e \u0939\u0948. \u0935\u0939\u0940\u0902 \u092a\u093f\u091b\u0932\u0947 5 \u0935\u0930\u094d\u0937\u094b\u0902 \u0938\u0947 \u091c\u0917\u0926\u0940\u0936\u092a\u0941\u0930 \u092e\u0947\u0902 \u0938\u0915\u094d\u0930\u093f\u092f \u0930\u0939\u0947 \u092c\u093f\u0939\u093e\u0930 \u0938\u0930\u0915\u093e\u0930 \u0915\u0947 \u092a\u0942\u0930\u094d\u0935 \u092e\u0902\u0924\u094d\u0930\u0940 \u092d\u0917\u0935\u093e\u0928 \u0938\u093f\u0902\u0939 \u0915\u0941\u0936\u0935\u093e\u0939\u093e \u091f\u093f\u0915\u091f \u0928\u0939\u0940\u0902 \u092e\u093f\u0932\u0928\u0947 \u0938\u0947 \u0928\u093e\u0930\u093e\u091c \u0939\u094b\u0915\u0930 \u090f\u0932\u091c\u0947\u092a\u0940 (LJP) \u0915\u0947 \u091f\u093f\u0915\u091f \u092a\u0930 \u092e\u0948\u0926\u093e\u0928 \u092e\u0947\u0902 \u0939\u0948\u0902. \u092d\u0917\u0935\u093e\u0928 \u0938\u093f\u0902\u0939 \u0915\u0941\u0936\u0935\u093e\u0939\u093e \u092f\u0939\u093e\u0902 \u0938\u0947 \u0924\u0940\u0928 \u092c\u093e\u0930 \u0935\u093f\u0927\u093e\u092f\u0915 \u0930\u0939 \u091a\u0941\u0915\u0947 \u0939\u0948\u0902. \u092e\u0939\u093e\u0917\u0920\u092c\u0902\u0927\u0928 \u0915\u0947 \u0918\u091f\u0915 \u0906\u0930\u091c\u0947\u0921\u0940 (RJD) \u0928\u0947 \u0905\u092a\u0928\u0947 \u0938\u093f\u091f\u093f\u0902\u0917 \u0935\u093f\u0927\u093e\u092f\u0915 \u0930\u093e\u092e \u0935\u093f\u0936\u0941\u0928 \u0938\u093f\u0902\u0939 \u0932\u094b\u0939\u093f\u092f\u093e \u0915\u094b \u090f\u0915 \u092c\u093e\u0930 \u092b\u093f\u0930 \u0938\u0947 \u092f\u0939\u093e\u0902 \u0938\u0947 \u0909\u092e\u094d\u092e\u0940\u0926\u0935\u093e\u0930 \u092c\u0928\u093e\u092f\u093e \u0939\u0948. \u0907\u0938 \u0915\u094d\u0937\u0947\u0924\u094d\u0930 \u0938\u0947 \u0935\u093f\u0927\u093e\u092f\u0915 \u0930\u0939 \u091a\u0941\u0915\u0947 \u0926\u093f\u0928\u0947\u0936 \u0915\u0941\u092e\u093e\u0930 \u092f\u093e\u0926\u0935 \u092d\u0940 \u091a\u0941\u0928\u093e\u0935\u0940 \u0926\u0902\u0917\u0932 \u092e\u0947\u0902 \u092d\u093e\u0917\u094d\u092f \u0906\u091c\u092e\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0909\u0924\u0930\u0947 \u0939\u0941\u090f \u0939\u0948\u0902.\n\u092c\u093f\u0939\u093e\u0930 \u0915\u0940 \u091c\u0917\u0926\u0940\u0936\u092a\u0941\u0930 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0940\u091f \u092d\u094b\u091c\u092a\u0941\u0930 \u091c\u093f\u0932\u0947 \u092e\u0947\u0902 \u0939\u0948. \u092f\u0939\u093e\u0902 28 \u0905\u0915\u094d\u091f\u0942\u092c\u0930 \u0915\u094b \u0935\u094b\u091f\u093f\u0902\u0917 \u0939\u094b\u0917\u0940. RJD \u0915\u0947 \u0930\u093e\u092e \u0935\u093f\u0936\u0941\u0928 \u0938\u093f\u0902\u0939 \u092f\u0939\u093e\u0902 \u0938\u0947 \u092e\u094c\u091c\u0942\u0926\u093e \u0935\u093f\u0927\u093e\u092f\u0915 \u0939\u0948\u0902. \u092a\u093f\u091b\u0932\u0947 \u091a\u0941\u0928\u093e\u0935 \u092e\u0947\u0902 RJD \u0915\u0947 \u0930\u093e\u092e \u0935\u093f\u0936\u0941\u0928 \u0938\u093f\u0902\u0939 \u0928\u0947 \u092f\u0939\u093e\u0902 \u0938\u0947 \u0930\u093e\u0932\u094b\u0938\u092a\u093e \u0915\u0947 \u0930\u093e\u0915\u0947\u0936 \u0930\u094c\u0936\u0928 \u0915\u094b 10,195 \u0935\u094b\u091f\u094b\u0902 \u0938\u0947 \u092a\u0940\u091b\u0947 \u091b\u094b\u0921\u093c\u0924\u0947 \u0939\u0941\u090f \u091c\u0940\u0924 \u0939\u093e\u0938\u093f\u0932 \u0915\u0940 \u0925\u0940. \u0907\u0938\u0938\u0947 \u092a\u0939\u0932\u0947 2010 \u092e\u0947\u0902 RJD \u0915\u0947 \u0926\u093f\u0928\u0947\u0936 \u0915\u0941\u092e\u093e\u0930 \u0938\u093f\u0902\u0939 \u092f\u0939\u093e\u0902 \u0938\u0947 \u091c\u0940\u0924\u0947 \u0925\u0947.\n\u0905\u0915\u094d\u091f\u0942\u092c\u0930 2005 \u092e\u0947\u0902 JDU \u0915\u0947 \u0936\u094d\u0930\u0940\u092d\u0917\u0935\u093e\u0928 \u0938\u093f\u0939 \u091a\u094c\u0925\u0940 \u092c\u093e\u0930 \u092f\u0939\u0902 \u0938\u0947 \u091c\u0940\u0924\u0947 \u0925\u0947. \u0907\u0938\u0938\u0947 \u092a\u0939\u0932\u0947 \u0935\u094b 1990 \u092e\u0947\u0902 \u092a\u0939\u0932\u0940 \u092c\u093e\u0930 \u0907\u0902\u0921\u093f\u092f\u0928 \u092a\u0940\u092a\u0941\u0932\u094d\u0938 \u092b\u094d\u0930\u0902\u091f \u0938\u0947, 2000 \u092e\u0947\u0902 \u0938\u092e\u0924\u093e \u092a\u093e\u0930\u094d\u091f\u0940 \u0938\u0947 \u0914\u0930 \u0924\u0940\u0938\u0930\u0940 \u092c\u093e\u0930 \u092b\u0930\u0935\u0930\u0940 2005 \u092e\u0947\u0902 JDU \u0938\u0947 \u091c\u0940\u0924\u0947 \u0925\u0947. \u0905\u092c \u0924\u0915 \u0939\u0941\u090f \u0915\u0941\u0932 \u091a\u0941\u0928\u093e\u0935\u094b\u0902 \u092e\u0947\u0902 2-2 \u092c\u093e\u0930 JDU, RJD \u0914\u0930 \u0928\u093f\u0930\u094d\u0926\u0932\u0940\u092f, 1-1 \u092c\u093e\u0930 \u0938\u092e\u0924\u093e \u092a\u093e\u0930\u094d\u091f\u0940, \u091c\u0928\u0924\u093e \u0926\u0932, \u0907\u0902\u0921\u093f\u092f\u0928 \u092a\u0940\u092a\u0941\u0932\u094d\u0938 \u092b\u094d\u0930\u0902\u091f \u0914\u0930 \u0932\u094b\u0915\u0926\u0932 \u0928\u0947 \u092f\u0939\u093e\u0902 \u0938\u0947 \u091c\u0940\u0924 \u0939\u093e\u0938\u093f\u0932 \u0915\u0940 \u0939\u0948.\n\u091c\u0917\u0926\u0940\u0936\u092a\u0941\u0930 \u0935\u093f\u0927\u093e\u0928\u0938\u092d\u093e \u0938\u0940\u091f \u092a\u0930 \u0938\u092c\u0938\u0947 \u0905\u0939\u092e \u092d\u0942\u092e\u093f\u0915\u093e \u092e\u0947\u0902 \u092f\u093e\u0926\u0935 \u0914\u0930 \u0930\u093e\u091c\u092a\u0942\u0924 \u0939\u0948\u0902. 2010 \u092e\u0947\u0902 \u092f\u0939\u093e\u0902 54.3 \u092a\u094d\u0930\u0924\u093f\u0936\u0924 \u0935\u094b\u091f\u093f\u0902\u0917 \u0939\u0941\u0908 \u0925\u0940. \u092a\u093f\u091b\u0932\u0947 \u091a\u0941\u0928\u093e\u0935 2015 \u092e\u0947\u0902 50.8 \u092a\u094d\u0930\u0924\u093f\u0936\u0924 \u092e\u0924\u0926\u093e\u0928 \u092f\u0939\u093e\u0902 \u0926\u0930\u094d\u091c \u0915\u093f\u092f\u093e \u0917\u092f\u093e \u0925\u093e.\n"}
diff --git a/sangraha/tok_sangraha/split/finalai_splitac b/sangraha/tok_sangraha/split/finalai_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..38c8daf8e6523562059a8beac4a949aa79235c95
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalai_splitac
@@ -0,0 +1 @@
+{"doc_id":"f75807c85b9cd1876fa237fed28eba9cb119c6991d09e74224c641338407c600","text":"\u0917\u093c\u091c\u093c\u0935\u093e-\u090f-\u0939\u093f\u0928\u094d\u0926 \u0915\u0947 \u0938\u0926\u093f\u092f\u094b\u0902 \u092a\u0941\u0930\u093e\u0928\u0947 \u0938\u092a\u0928\u0947 \u0915\u094b \u0938\u093e\u0915\u093e\u0930 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u092f\u0947 \u0935\u0943\u0939\u0924\u094d\u0924\u0930 \u092d\u093e\u0930\u0924 \u092a\u0930 \u0935\u093f\u092d\u093f\u0928\u094d\u0928 \u0924\u0915\u0928\u0940\u0915\u0947\u0902 \u0938\u0948\u0915\u0921\u093c\u094b\u0902 \u0935\u0930\u094d\u0937\u094b\u0902 \u0938\u0947 \u092a\u094d\u0930\u092f\u094b\u0917 \u092e\u0947\u0902 \u0932\u093e\u092f\u0940 \u091c\u093e \u0930\u0939\u0940 \u0939\u0948\u0902\u0964\n\u0917\u093c\u091c\u093c\u0935\u093e-\u090f-\u0939\u093f\u0928\u094d\u0926 \u0915\u0947 \u0938\u0926\u093f\u092f\u094b\u0902 \u092a\u0941\u0930\u093e\u0928\u0947 \u0938\u092a\u0928\u0947 \u0915\u094b \u0938\u093e\u0915\u093e\u0930 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u092f\u0947 \u0935\u0943\u0939\u0924\u094d\u0924\u0930 \u092d\u093e\u0930\u0924 \u092a\u0930 \u0935\u093f\u092d\u093f\u0928\u094d\u0928 \u0924\u0915\u0928\u0940\u0915\u0947\u0902 \u0938\u0948\u0915\u0921\u093c\u094b\u0902 \u0935\u0930\u094d\u0937\u094b\u0902 \u0938\u0947 \u092a\u094d\u0930\u092f\u094b\u0917 \u092e\u0947\u0902 \u0932\u093e\u092f\u0940 \u091c\u093e \u0930\u0939\u0940 \u0939\u0948\u0902\u0964 \u0909\u0928\u094d\u0939\u0940\u0902 \u092e\u0947\u0902 \u0938\u0947 \u090f\u0915 \u092a\u094d\u0930\u092e\u0941\u0916 \u0924\u0915\u0928\u0940\u0915 \u0936\u0924\u094d\u0930\u0941 \u092a\u0915\u094d\u0937 \u092e\u0947\u0902 \u0935\u093f\u092d\u093e\u091c\u0928 \u0915\u0940 \u0924\u0915\u0928\u0940\u0915 \u0939\u0948\u0964 \u0906\u092a\u0915\u094b \u092a\u0902\u091a\u0924\u0902\u0924\u094d\u0930 \u0915\u0940 \u092c\u0942\u0922\u093c\u0947 \u092a\u093f\u0924\u093e \u0914\u0930 \u0909\u0938\u0915\u0947 \u091a\u093e\u0930 \u092c\u0947\u091f\u094b\u0902 \u0915\u0940 \u0915\u0939\u093e\u0928\u0940 \u0927\u094d\u092f\u093e\u0928 \u0939\u094b\u0917\u0940\u0964 \u092c\u0942\u0922\u093c\u093e \u0905\u092a\u0928\u0947 \u0906\u092a\u0938 \u092e\u0947\u0902 \u091d\u0917\u0921\u093c\u0928\u0947 \u0935\u093e\u0932\u0947 \u092c\u0947\u091f\u094b\u0902 \u0915\u094b \u092c\u0941\u0932\u093e \u0915\u0930 10-12 \u092a\u0924\u0932\u0940-\u092a\u0924\u0932\u0940 \u0932\u0915\u0921\u093c\u093f\u092f\u094b\u0902 \u0915\u0947 \u092c\u0902\u0927\u0947 \u0939\u0941\u090f \u0917\u091f\u094d\u0920\u0930 \u0915\u094b \u0924\u094b\u0921\u093c\u0928\u0947 \u0915\u0947 \u0932\u093f\u092f\u0947 \u0926\u0947\u0924\u093e \u0939\u0948\u0964 \u0938\u093e\u0930\u0947 \u092c\u0947\u091f\u0947 \u090f\u0915-\u090f\u0915 \u0915\u0930\u0915\u0947 \u0905\u0938\u092b\u0932 \u0939\u094b \u091c\u093e\u0924\u0947 \u0939\u0948\u0902\u0964 \u092b\u093f\u0930 \u0935\u094b \u0917\u091f\u094d\u0920\u0930 \u0915\u094b 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\u0939\u0948\u0902\u0964 \u0907\u0928\u0915\u0940 \u092d\u0902\u0917\u0940, \u091a\u0942\u0939\u0921\u093c, \u092e\u0947\u0939\u0924\u0930, \u0939\u0932\u093e\u0932\u0916\u094b\u0930 \u092a\u094d\u0930\u092e\u0941\u0916 \u0936\u093e\u0916\u093e\u090f\u0902 \u0939\u0948\u0902\u0964 \u0907\u0928\u0915\u0940 \u0915\u093f\u0938\u094d\u092e\u094b\u0902, \u0917\u094b\u0924\u094d\u0930\u094b\u0902 \u0915\u0947 \u0928\u093e\u092e \u092c\u0941\u0902\u0926\u0947\u0932\u093f\u092f\u093e, \u092f\u0926\u0941\u0935\u0902\u0936\u0940, \u0928\u093e\u0926\u094b\u0902, \u092d\u0926\u094c\u0930\u093f\u092f\u093e, \u091a\u094c\u0939\u093e\u0928, \u0915\u093f\u0928\u0935\u093e\u0930 \u0920\u093e\u0915\u0941\u0930, \u092c\u0948\u0938, \u0917\u0947\u0939\u0932\u094c\u0924\u093e, \u0917\u0939\u0932\u094b\u0924, \u091a\u0902\u0926\u0947\u0932, \u0935\u0948\u0938, \u0935\u0948\u0938\u0935\u093e\u0930, \u092c\u0940\u0930 \u0917\u0942\u091c\u0930 \u092f\u093e \u092c\u0917\u094d\u0917\u0942\u091c\u0930, \u0915\u091b\u0935\u093e\u0939\u093e, \u0917\u093e\u091c\u0940\u092a\u0941\u0930\u0940 \u0930\u093e\u0909\u0924, \u091f\u093f\u092a\u0923\u0940, \u0916\u0930\u093f\u092f\u093e, \u0915\u093f\u0928\u0935\u093e\u0930-\u0920\u093e\u0915\u0941\u0930, \u0926\u093f\u0928\u093e\u092a\u0941\u0930\u0940 \u0930\u093e\u0909\u0924, \u091f\u093e\u0902\u0915, \u092e\u0947\u0939\u0924\u0930, \u092d\u0902\u0917\u0940, \u0939\u0932\u093e\u0932 \u0907\u0924\u094d\u092f\u093e\u0926\u093f \u0939\u0948\u0902\u0964 \u0915\u094d\u092f\u093e \u0907\u0928 \u0915\u093c\u093f\u0938\u094d\u092e\u094b\u0902 \u0915\u0947 \u0928\u093e\u092e \u092a\u0922\u093c \u0915\u0930 \u0907\u0938 \u0935\u0940\u0930\u0924\u093e \u0915\u093e, \u091c\u0942\u091d\u093e\u0930\u0942 \u0939\u094b\u0928\u0947 \u0915\u093e \u0915\u093e\u0930\u0923 \u0938\u092e\u091d \u092e\u0947\u0902 \u0928\u0939\u0940\u0902 \u0906\u0924\u093e ? \u092c\u0902\u0927\u0941\u0913 \u092f\u0947 \u0938\u093e\u0930\u0947 \u0917\u094b\u0924\u094d\u0930 \u092d\u0930\u0924\u0935\u0902\u0936\u0940 \u0915\u094d\u0937\u0924\u094d\u0930\u093f\u092f\u094b\u0902 \u0915\u0947 \u091c\u0948\u0938\u0947 \u0928\u0939\u0940\u0902 \u0932\u0917\u0924\u0947 \u0939\u0948\u0902 ? \u0915\u093f\u0938\u0940 \u0915\u094b \u0936\u0915 \u0939\u094b \u0924\u094b \u0915\u093f\u0938\u0940 \u092d\u0940 \u0920\u093e\u0915\u0941\u0930 \u0915\u0947 \u0938\u093e\u0925 \u092c\u093e\u0924 \u0915\u0930\u0915\u0947 \u0924\u0938\u094d\u0926\u0940\u0915\u093c \u0915\u0940 \u091c\u093e \u0938\u0915\u0924\u0940 \u0939\u0948\u0964 \u0907\u0928 \u0905\u0928\u0941\u0938\u0942\u091a\u093f\u0924 \u091c\u093e\u0924\u093f\u092f\u094b\u0902 \u092e\u0947\u0902 \u092f\u0947 \u0928\u093e\u092e \u0907\u0928\u092e\u0947\u0902 \u0915\u0939\u093e\u0901 \u0938\u0947 \u0906 \u0917\u092f\u0947 ? \u0910\u0938\u093e \u0915\u094d\u092f\u094b\u0902 \u0939\u0948 \u0915\u093f \u0905\u0928\u0941\u0938\u0942\u091a\u093f\u0924 \u091c\u093e\u0924\u093f\u092f\u094b\u0902 \u0915\u0940 \u092f\u0947 \u0915\u093c\u093f\u0938\u094d\u092e\u0947\u0902 \u0909\u0924\u094d\u0924\u0930 \u092a\u094d\u0930\u0926\u0947\u0936, \u092c\u093f\u0939\u093e\u0930, \u092c\u0902\u0917\u093e\u0932, \u092e\u0927\u094d\u092f \u092a\u094d\u0930\u0926\u0947\u0936 \u092e\u0947\u0902 \u0939\u0940 \u0939\u0948\u0902 ? \u091c\u094b \u0907\u0932\u093e\u0915\u093c\u0947 \u0938\u0940\u0927\u0947 \u092e\u0941\u0938\u094d\u0932\u093f\u092e \u0906\u0915\u094d\u0930\u092e\u0923\u0915\u093e\u0930\u093f\u092f\u094b\u0902 \u0938\u0947 \u0938\u0926\u093f\u092f\u094b\u0902 \u091c\u0942\u091d\u0924\u0947 \u0930\u0939\u0947 \u0939\u0948\u0902 \u0909\u0928\u094d\u0939\u0940\u0902 \u092e\u0947\u0902 \u092f\u0947 \u0917\u094b\u0924\u094d\u0930 \u0915\u094d\u092f\u094b\u0902 \u092e\u093f\u0932\u0924\u0947 \u0939\u0948\u0902 ? \u0939\u0932\u093e\u0932\u0916\u094b\u0930 \u0936\u092c\u094d\u0926 \u0905\u0930\u092c\u0940 \u0939\u0948\u0964 \u092d\u093e\u0930\u0924 \u0915\u0940 \u0915\u093f\u0938\u0940 \u091c\u093e\u0924\u093f \u0915\u093e \u0928\u093e\u092e \u0905\u0930\u092c\u0940 \u092e\u0942\u0932 \u0915\u093e \u0915\u0948\u0938\u0947 \u0939\u0948 ? \u0915\u094d\u092f\u093e \u0905\u0930\u092c\u0940 \u0906\u0915\u094d\u0930\u092e\u0923\u0915\u093e\u0930\u093f\u092f\u094b\u0902 \u092f\u093e \u0905\u0930\u092c\u0940 \u0938\u094b\u091a \u0930\u0916\u0928\u0947 \u0935\u093e\u0932\u0947 \u0932\u094b\u0917\u094b\u0902 \u0928\u0947 \u092f\u0947 \u091c\u093e\u0924\u093f \u092c\u0928\u093e\u092f\u0940 \u0925\u0940 ? \u0907\u0928\u094d\u0939\u0947\u0902 \u092d\u0902\u0917\u0940 \u0915\u094d\u092f\u094b\u0902 \u0915\u0939\u093e \u0917\u092f\u093e \u0939\u094b\u0917\u093e ? \u092f\u0947 \u0936\u0941\u0926\u094d\u0927 \u0938\u0902\u0938\u094d\u0915\u0943\u0924 \u0936\u092c\u094d\u0926 \u0939\u0948 \u0914\u0930 \u0907\u0938\u0915\u093e \u0905\u0930\u094d\u0925 '\u0935\u0939 \u091c\u093f\u0938\u0928\u0947 \u092d\u0902\u0917 \u0915\u093f\u092f\u093e \u092f\u093e \u0924\u094b\u0921\u093c\u093e' \u0939\u094b\u0924\u093e \u0939\u0948\u0964 \u0907\u0928\u094d\u0939\u094b\u0928\u0947 \u0915\u094d\u092f\u093e \u092d\u0902\u0917 \u0915\u093f\u092f\u093e \u0925\u093e \u091c\u093f\u0938\u0915\u0947 \u0915\u093e\u0930\u0923 \u0907\u0928\u094d\u0939\u094b\u0928\u0947 \u092f\u0947 \u0928\u093e\u092e \u0938\u094d\u0935\u0940\u0915\u093e\u0930 \u0915\u093f\u092f\u093e\u0964\n"}
diff --git a/sangraha/tok_sangraha/split/finalak_splitac b/sangraha/tok_sangraha/split/finalak_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..24c98f182ea67c855d253ebadc5df7c1480ae061
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalak_splitac
@@ -0,0 +1 @@
+{"doc_id":"592c24e81ff95e86e5d250041887c7849da5299a254caf70639fe15d28720b24","text":"\u0928\u0908 \u0926\u093f\u0932\u094d\u0932\u0940\u0964 \u0907\u0928 \u0926\u093f\u0928\u094b\u0902 \u0915\u0908 \u092c\u093e\u0930 \u0910\u0938\u0940 \u0918\u091f\u0928\u093e\u090f\u0902 \u0938\u0941\u0928\u0928\u0947 \u0914\u0930 \u0926\u0947\u0916\u0928\u0947 \u0915\u094b \u092e\u093f\u0932\u0924\u0940 \u0939\u0948 \u091c\u092c \u0930\u093e\u0939 \u091a\u0932\u0924\u0947 \u0907\u0902\u0938\u093e\u0928 \u0915\u093e \u0938\u093e\u092e\u0928\u093e \u0915\u093f\u0938\u0940 \u091c\u0902\u0917\u0932\u0940 \u091c\u093e\u0928\u0935\u0930 \u0938\u0947 \u0939\u094b \u091c\u093e\u0924\u093e \u0939\u0948\u0964 \u091c\u093f\u0938 \u0915\u093f\u0938\u0940 \u0915\u0947 \u0938\u093e\u0925 \u092d\u0940 \u0910\u0938\u093e \u0939\u094b\u0924\u093e \u0939\u0948 \u090f\u0915 \u092c\u093e\u0930 \u0924\u094b \u0909\u0938\u0915\u0947 \u0939\u094b\u0936 \u0909\u0921\u093c \u091c\u093e\u0924\u0947 \u0939\u0948\u0902\u0964 \u0915\u0908 \u092e\u094c\u0915\u094b\u0902 \u092a\u0930 \u0924\u094b \u092f\u0939 \u0905\u0924\u094d\u092f\u0902\u0924 \u0918\u093e\u0924\u0915 \u0938\u093e\u092c\u093f\u0924 \u0939\u094b\u0924\u093e \u0939\u0948 \u0932\u0947\u0915\u093f\u0928 \u0915\u0941\u091b\u0947\u0915 \u0905\u0935\u0938\u0930\u094b\u0902 \u092a\u0930 \u092d\u093e\u0917\u094d\u092f \u0938\u093e\u0925 \u0926\u0947\u0928\u0947 \u0938\u0947 \u092c\u093e\u0932 \u092d\u0940 \u092c\u093e\u0902\u0915\u093e \u0928\u0939\u0940\u0902 \u0939\u094b\u0924\u093e\u0964\n\u0906\u091c \u0939\u092e \u0906\u092a\u0915\u094b \u091a\u0940\u0928 \u0915\u0947 \u0936\u0939\u0930 \u092f\u0942\u0928\u093e\u0928 \u0915\u0940 \u090f\u0915 \u0910\u0938\u0940 \u0939\u0940 \u0918\u091f\u0928\u093e \u0915\u0947 \u092c\u093e\u0930\u0947 \u092e\u0947\u0902 \u092c\u0924\u093e\u0928\u0947 \u091c\u093e \u0930\u0939\u0947 \u0939\u0948\u0902, \u091c\u093f\u0938\u092e\u0947\u0902 \u0939\u093e\u0925\u0940 \u0905\u091a\u093e\u0928\u0915 \u0938\u0921\u0915\u093c \u0915\u0947 \u092c\u0940\u091a\u094b\u0902 \u092c\u0940\u091a \u0906 \u0917\u092f\u093e\u0964 \u0909\u0938\u0947 \u0935\u0939\u093e\u0902 \u090f\u0915 \u092c\u0938 \u0926\u093f\u0916\u0940, \u091c\u093f\u0938\u092e\u0947\u0902 \u0938\u093f\u0930\u094d\u092b \u0921\u094d\u0930\u093e\u0908\u0935\u0930 \u092c\u0948\u0920\u093e \u0925\u093e\u0964 \u0939\u093e\u0925\u0940 \u0928\u0947 \u092a\u0939\u0932\u0947 \u0924\u094b \u092c\u0938 \u0915\u094b \u0928\u093f\u0939\u093e\u0930\u093e \u0914\u0930 \u092b\u093f\u0930 \u0909\u0938\u0947 \u0927\u0915\u094d\u0915\u093e \u0926\u0947\u0915\u0930 \u0906\u0917\u0947 \u0938\u0930\u0915\u093e \u0926\u093f\u092f\u093e\u0964 \u0935\u0939 \u092f\u0939\u0940\u0902 \u0928\u0939\u0940\u0902 \u0930\u0941\u0915\u093e \u0914\u0930 \u0938\u0942\u0902\u0921 \u0938\u0947 \u0935\u093f\u0902\u0921\u0936\u0940\u0932\u094d\u0921 \u092a\u0930 \u091c\u094b\u0930 \u0938\u0947 \u0935\u093e\u0930 \u0915\u0930 \u0915\u093e\u0902\u091a \u0924\u094b\u0921\u093c \u0926\u093f\u092f\u093e\u0964 \u0907\u0938\u0915\u0947 \u092c\u093e\u0926 \u0909\u0938\u0928\u0947 \u092c\u0938 \u0938\u0947 \u0939\u0940 \u0905\u092a\u0928\u0947 \u0936\u0930\u0940\u0930 \u0915\u094b \u0930\u0917\u0921\u093c-\u0930\u0917\u0921\u0915\u093c\u0930 \u0916\u0941\u091c\u0932\u0940 \u092e\u093f\u091f\u093e\u0908\u0964\n"}
diff --git a/sangraha/tok_sangraha/split/finalal_splitac b/sangraha/tok_sangraha/split/finalal_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..0898594e9d390c7383fb500ebdcfd1b441d0a106
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalal_splitac
@@ -0,0 +1 @@
+{"doc_id":"9072ee8f7604344388f2ba73ea8e2865c6cfca0363b0ec662a5e9bf7e5e3322c","text":"\u092e\u0941\u0902\u092c\u0908\/\u092d\u093e\u0937\u093e\u0964 \u0905\u0926\u093e\u0915\u093e\u0930\u093e \u0915\u0930\u0940\u0928\u093e \u0915\u092a\u0942\u0930 \u0916\u093e\u0928 \u0915\u093e \u0915\u0939\u0928\u093e \u0939\u0948 \u0915\u093f \u092b\u093f\u0932\u094d\u092e \u0909\u0926\u094d\u092f\u094b\u0917 \u092e\u0947\u0902 \u0915\u093f\u0938\u0940 \u0915\u0947 \u0932\u093f\u090f \u0926\u0942\u0938\u0930\u0947 \u0915\u0940 \u0908\u092e\u093e\u0928\u0926\u093e\u0930\u0940 \u0915\u093e \u0920\u0947\u0915\u093e \u0932\u0947\u0928\u093e \u0905\u0938\u0902\u092d\u0935 \u0939\u0948 \u0915\u094d\u092f\u094b\u0902\u0915\u093f \u0932\u094b\u0917 \u0906\u0932\u094b\u091a\u0928\u093e \u0915\u093e \u0938\u094d\u0935\u093e\u0917\u0924 \u0928\u0939\u0940\u0902 \u0915\u0930\u0924\u0947\u0964 \u0909\u0928\u0915\u093e \u092e\u093e\u0928\u0928\u093e \u0939\u0948 \u0915\u093f \u092b\u093f\u0932\u094d\u092e\u0940 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diff --git a/sangraha/tok_sangraha/split/finalam_splitac b/sangraha/tok_sangraha/split/finalam_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..b65e2c0252a32445d64233a2c6807a52240f475c
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalam_splitac
@@ -0,0 +1 @@
+{"doc_id":"6eff05e8063a12d7514e1f4441b903139bb28a7e3dd567b6d09c4fa191f65b30","text":"\u092a\u0930\u094d\u092f\u093e\u0935\u0930\u0923 \u091f\u0940\u092e \u0915\u0947 \u0938\u0926\u0938\u094d\u092f \u0915\u093f\u0938\u0940 \u092d\u0940 \u0905\u0928\u094d\u092f \u0935\u094d\u092f\u0915\u094d\u0924\u093f \u0938\u0947 \u0928\u0939\u0940\u0902 \u0939\u094b\u0924\u0947 \u0939\u0948\u0902\u0964 \u0939\u093e\u0932 \u0939\u0940 \u092e\u0947\u0902 \u090f\u0915 \u0935\u0940\u0921\u093f\u092f\u094b \u0938\u094b\u0936\u0932 \u092e\u0940\u0921\u093f\u092f\u093e \u092a\u0930 \u0924\u0947\u091c\u0940 \u0938\u0947 \u0924\u0947\u091c \u0939\u094b \u0930\u0939\u093e \u0939\u0948\u0964 \u0915\u0948\u092e\u0930\u0947 \u0915\u0940 \u091c\u093e\u0902\u091a \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0935\u093f\u0936\u0947\u0937 \u0930\u0942\u092a \u0938\u0947 \u0928\u093f\u092f\u0902\u0924\u094d\u0930\u093f\u0924 \u0939\u094b\u0924\u0947 \u0939\u0948\u0902\u0964 \u0938\u094d\u0935\u0938\u094d\u0925 \u0930\u0939\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0909\u092a\u092f\u0941\u0915\u094d\u0924 \u0939\u0948\u0902\u0964\n\u0935\u0940\u0921\u093f\u092f\u094b \u092e\u0947\u0902 \u0910\u0938\u093e \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0910\u0938\u0940 \u0938\u094d\u0925\u093f\u0924\u093f \u092e\u0947\u0902 \u0938\u094d\u0925\u093f\u0924\u093f \u0915\u094b \u0928\u093f\u092f\u0902\u0924\u094d\u0930\u093f\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0910\u0938\u0940 \u0938\u094d\u0925\u093f\u0924\u093f \u092e\u0947\u0902 \u0915\u094d\u092f\u093e \u0915\u093f\u092f\u093e \u091c\u093e \u0938\u0915\u0924\u093e \u0939\u0948\u0964 \u0907\u0938 \u0935\u0940\u0921\u093f\u092f\u094b \u092e\u0947\u0902 \u0926\u094b \u0905\u0932\u0917-\u0905\u0932\u0917-\u0905\u0932\u0917-\u0905\u0932\u0917 \u0935\u0940\u0921\u093f\u092f\u094b \u0915\u093e \u0915\u094b\u0932\u093e\u091c \u0926\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u090f\u0915 \u0935\u0940\u0921\u093f\u092f\u094b \u092e\u0947\u0902 \u091c\u093e\u0902\u091a \u0915\u0930 \u0930\u0939\u0947 \u0939\u0948\u0902 I \u0935\u0940\u0921\u093f\u092f\u094b \u092e\u0947\u0902 \u0938\u0941\u0928\u093f\u0936\u094d\u091a\u093f\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f, \u0909\u0928\u094d\u0939\u0947\u0902 \u0926\u0947\u0916\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u092b\u093f\u0930 \u092d\u0940, \u0935\u0939 \u0938\u092e\u092f \u092a\u0930 \u092d\u0940 \u0905\u092a\u0921\u0947\u091f \u0926\u093f\u0916\u093e\u0908 \u0926\u0947\u0924\u093e \u0939\u0948\u0964\n\u0935\u0940\u0921\u093f\u092f\u094b \u0915\u0947 \u0905\u0902\u0924 \u092e\u0947\u0902 \u0930\u093f\u0915\u0949\u0930\u094d\u0921\u093f\u0902\u0917, \"\u091a\u0932\u094b \u0905\u092c \u092d\u0940 \u0905\u092c \u092d\u0940 \u0930\u093f\u0915\u0949\u0930\u094d\u0921\u093f\u0902\u0917 \u0915\u0947 \u092c\u093e\u0926\u0964\" VIDEO, \u0935\u0940\u0921\u093f\u092f\u094b \u0915\u094b \u0936\u0947\u092f\u0930 \u0915\u0930\u0924\u0947 \u0939\u0941\u090f \u0905\u0928\u0941\u0937\u094d\u0915 \u0928\u0947 \u0932\u093f\u0916\u093e, \"\u092e\u0941\u091d\u0938\u0947 \u0915\u0947 \u0938\u093e\u0925 \u091f\u0915\u093e \u091f\u0915\u093e \u092e\u0947\u0902 \u091a\u093e\u0932 \u0916\u0930\u093e\u092c \u0939\u094b\u0964 \u0938\u094b\u0936\u0932 \u092e\u093f\u0921\u093f\u092f\u093e \u092a\u0930 \u0932\u093e\u0917\u0942 \u0939\u094b\u0928\u0947 \u0935\u093e\u0932\u093e \u0939\u0948 I \u0935\u093f\u091c\u092f\u093e \u0915\u0940 \u091c\u0940\u0924.\n\u0907\u0938 \u0938\u092e\u092f \u0915\u0947 \u0932\u093f\u090f \u0936\u093e\u0928\u0926\u093e\u0930 \u0939\u0948\u0902 \u0914\u0930 \u0907\u0938 \u0938\u092e\u092f \u0932\u0902\u0926\u0928 \u092e\u0947\u0902 \u0939\u0948\u0902\u0964 \u092a\u0941\u0924\u094d\u0930\u0940 \u0935\u093e\u092e\u093f\u0915\u093e \u0915\u0947 \u091c\u0928\u094d\u092e \u0915\u0947 \u092c\u093e\u0926, \u0938\u094b\u0936\u0932 \u092e\u0940\u0921\u093f\u092f\u093e \u092a\u0930 \u0906\u0901\u0915\u0921\u093c\u094b\u0902 \u0915\u093e \u092a\u094d\u0930\u092d\u093e\u0935 \u092a\u0921\u093c\u0924\u093e \u0939\u0948\u0964 \u0935\u0947 \u0938\u092e\u092f \u092a\u0930 \u0915\u0947 \u0938\u093e\u0925 \u092b\u094b\u091f\u094b\u091c \u0914\u0930 \u0935\u0940\u0921\u093f\u092f\u094b\u091c \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u092a\u0930\u093f\u0935\u093e\u0930 \u0915\u0947 \u0938\u093e\u0925 \u092e\u093f\u0932\u0915\u0930 \u0915\u093e\u092e \u0915\u0930\u0924\u0947 \u0939\u0948\u0902\u0964\n(Renewed) HP EliteBook 14 inch (35.56 cm) HD Laptop (i5 4th Gen\/8 GB RAM\/256 GB SSD\/Wifi\/Bluetooth 4.0\/Windows 10 Pro\/MS Office\/Webcam\/Integrated Graphics)\n"}
diff --git a/sangraha/tok_sangraha/split/finalan_splitac b/sangraha/tok_sangraha/split/finalan_splitac
new file mode 100644
index 0000000000000000000000000000000000000000..bc67139e23cf747f308dfc300aecf0395e169a6f
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalan_splitac
@@ -0,0 +1 @@
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\u0926\u093f\u0932\u093e\u092f\u093e\u0964\n\u0928\u094c\u091c\u0935\u093e\u0928\u094b\u0902 \u0928\u0947 \u0939\u093f\u092e\u093e\u092f\u0924\u0941\u0932\u094d\u0932\u093e\u0939 \u092a\u0930 \u0915\u0947\u0938 \u0926\u0930\u094d\u091c \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u092d\u0940 \u092f\u093e\u0926\u094d\u0926\u093e\u0936\u094d\u0924 \u092a\u0947\u0936 \u0915\u0940 \u0914\u0930 \u0906\u0930 \u0921\u0940 \u0913 \u0915\u094b \u0939\u0941\u0915\u0942\u092e\u0924 \u0938\u0924\u0939 \u092a\u0930 \u0928\u0941\u092e\u093e\u0907\u0902\u0926\u0917\u0940 \u0915\u0930\u0928\u0947 \u0914\u0930 \u0935\u0915\u093c\u094d\u092b\u093c \u092c\u094b\u0930\u094d\u0921 \u0915\u0940 \u091c\u093e\u0928\u093f\u092c \u0938\u0947 \u0909\u0928\u094d\u0939\u0947\u0902 \u0916\u093c\u093e\u0930\u093f\u091c \u0915\u0930\u0928\u0947 \u0915\u0947 \u092c\u093e\u0930\u0947 \u092e\u0947\u0902 \u092d\u0940 \u0935\u093e\u0915\u093c\u093f\u092b\u093c \u0915\u0930\u0935\u093e\u092f\u093e\u0964\n"}
diff --git a/sangraha/tok_sangraha/split/finalap b/sangraha/tok_sangraha/split/finalap
new file mode 100644
index 0000000000000000000000000000000000000000..d6dd52cf7599517b8e05e878c027a138179cb243
--- /dev/null
+++ b/sangraha/tok_sangraha/split/finalap
@@ -0,0 +1,5 @@
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+{"doc_id":"3015348441ebbb429e1e963ae14eef34565b45a54e3ff21efbd5e9f910a1a3b1","text":"\u091a\u0940\u0928\u0940 \u0938\u094d\u092e\u093e\u0930\u094d\u091f\u092b\u094b\u0928 \u0928\u093f\u0930\u094d\u092e\u093e\u0924\u093e \u0915\u0902\u092a\u0928\u0940 xiaomi \u0915\u0947 \u0907\u0938 \u0928\u090f \u092e\u0949\u0921\u0932 \u092e\u0940 \u092e\u0948\u0915\u094d\u0938 2 \u0938\u094d\u092e\u093e\u0930\u094d\u091f\u092b\u094b\u0928 \u0915\u093e \u0928\u092f\u093e \u0905\u0935\u0924\u093e\u0930 \u0932\u093e\u0902\u091a \u0915\u093f\u092f\u093e \u0939\u0948. \u0905\u0917\u0930 \u0906\u092a \u0907\u0938 \u0928\u090f \u0915\u0932\u0930 \u0938\u0947 \u0915\u093e\u092b\u0940 \u0905\u091f\u094d\u0930\u0948\u0915\u094d\u091f \u0939\u094b \u0930\u0939\u0947 \u0939\u0948. \u0924\u094b \u091c\u093e\u0928 \u0932\u0940\u091c\u093f\u090f, \u0906\u0916\u093f\u0930 \u0915\u094d\u092f\u093e \u0939\u0948 xiaomi \u092e\u0940 \u092e\u0948\u0915\u094d\u0938 2 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\u0932\u093f\u092f\u0947 \u0907\u0928\u092c\u093f\u0932\u094d\u091f \u0938\u094d\u091f\u094b\u0930\u0947\u091c \u092e\u0947\u0902 64 \u091c\u0940\u092c\u0940 \u0914\u0930 128 \u091c\u0940\u092c\u0940 \u0915\u093e \u0935\u093f\u0915\u0932\u094d\u092a \u092e\u094c\u091c\u0942\u0926 \u0939\u0948. \u0928\u090f \u0905\u0935\u0924\u093e\u0930 \u092e\u0948\u091f\u0947 \u092c\u094d\u0932\u0948\u0915 \u0915\u0932\u0930 \u092e\u0947\u0902 \u092f\u0942\u091c\u0930 \u0915\u0947 \u0932\u093f\u092f\u0947 64 \u091c\u0940\u092c\u0940 \u0935\u093e\u0932\u093e \u0938\u094d\u092e\u093e\u0930\u094d\u091f\u092b\u094b\u0928 \u0932\u0947 \u092a\u093e\u090f\u0902\u0917\u0947. \u0907\u0938 \u0938\u094d\u092e\u093e\u0930\u094d\u091f\u092b\u094b\u0928 \u0915\u0940 \u0926\u0942\u0938\u0930\u0940 \u0916\u093e\u0938\u093f\u092f\u0924 \u0907\u0938\u092e\u0947\u0902 \u092e\u094c\u091c\u0942\u0926\u093e \u092b\u093c\u093e\u0938\u094d\u091f \u091a\u093e\u0930\u094d\u091c\u093f\u0902\u0917 \u0915\u093e \u0938\u092a\u094b\u0930\u094d\u091f \u0939\u0948. \u0915\u0902\u092a\u0928\u0940 \u0915\u0947 \u092e\u0941\u0924\u093e\u092c\u093f\u0915 \u092c\u0948\u091f\u0930\u0940 \u0932\u093e\u0907\u092b \u0968 \u0926\u093f\u0928 \u0924\u0915 \u091a\u0932\u0928\u0947 \u0915\u093e \u0926\u0935\u093e \u0915\u093f\u092f\u093e \u0917\u092f\u093e.\n"}
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_0.sh b/sangraha/tok_sangraha/tok_files/tokenizer_0.sh
new file mode 100644
index 0000000000000000000000000000000000000000..bc5d7be3dbaf57db2e90c55765f9f313313b9d59
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_0.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer0/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer0/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_1.sh b/sangraha/tok_sangraha/tok_files/tokenizer_1.sh
new file mode 100644
index 0000000000000000000000000000000000000000..eb9b29e4b6569504a8c699ec0db963e282499cd9
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_1.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer1/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitab \
+ --output-prefix $FINAL_DIR/tokenizer1/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_10.sh b/sangraha/tok_sangraha/tok_files/tokenizer_10.sh
new file mode 100644
index 0000000000000000000000000000000000000000..538eaff70be4f53510277e1f8fa925afec4afbaf
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_10.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer10/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitab \
+ --output-prefix $FINAL_DIR/tokenizer10/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_11.sh b/sangraha/tok_sangraha/tok_files/tokenizer_11.sh
new file mode 100644
index 0000000000000000000000000000000000000000..95b26f9c3c8bc465ca07fd3636b5d1fd42b23c83
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_11.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer11/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitac \
+ --output-prefix $FINAL_DIR/tokenizer11/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_12.sh b/sangraha/tok_sangraha/tok_files/tokenizer_12.sh
new file mode 100644
index 0000000000000000000000000000000000000000..79f5d037d0056696d8b27a314e4ba2c3d5ce86e6
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_12.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer12/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer12/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_13.sh b/sangraha/tok_sangraha/tok_files/tokenizer_13.sh
new file mode 100644
index 0000000000000000000000000000000000000000..a8d193008601c22001f88affb257e7035212d0f5
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_13.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer13/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitab \
+ --output-prefix $FINAL_DIR/tokenizer13/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_14.sh b/sangraha/tok_sangraha/tok_files/tokenizer_14.sh
new file mode 100644
index 0000000000000000000000000000000000000000..84f13937598c60cfe8063d3a6959188c8a37af24
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_14.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer14/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalae_splitac \
+ --output-prefix $FINAL_DIR/tokenizer14/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_15.sh b/sangraha/tok_sangraha/tok_files/tokenizer_15.sh
new file mode 100644
index 0000000000000000000000000000000000000000..e4da71ec8fe98e95a3447996146d19d5dc108c74
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_15.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer15/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer15/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_16.sh b/sangraha/tok_sangraha/tok_files/tokenizer_16.sh
new file mode 100644
index 0000000000000000000000000000000000000000..8e9b1d6fbbf7524f227d301487bfebc5cac3f1c1
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_16.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer16/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitab \
+ --output-prefix $FINAL_DIR/tokenizer16/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_17.sh b/sangraha/tok_sangraha/tok_files/tokenizer_17.sh
new file mode 100644
index 0000000000000000000000000000000000000000..7d49f9f0692f0134a038f71b91902f757afd1b51
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_17.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer17/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaf_splitac \
+ --output-prefix $FINAL_DIR/tokenizer17/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_18.sh b/sangraha/tok_sangraha/tok_files/tokenizer_18.sh
new file mode 100644
index 0000000000000000000000000000000000000000..91d4fc13d964910442b497908c377904b6305e36
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_18.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer18/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer18/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_19.sh b/sangraha/tok_sangraha/tok_files/tokenizer_19.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5e5b0f3048560ad60e562a7001f71a9fb3cf5d58
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_19.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer19/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitab \
+ --output-prefix $FINAL_DIR/tokenizer19/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_2.sh b/sangraha/tok_sangraha/tok_files/tokenizer_2.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5189f86f5eaa27b09bfd9783fec43ad4d02a53f7
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_2.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer2/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaa_splitac \
+ --output-prefix $FINAL_DIR/tokenizer2/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_20.sh b/sangraha/tok_sangraha/tok_files/tokenizer_20.sh
new file mode 100644
index 0000000000000000000000000000000000000000..57846fa71b8a91e102cdf7463074d88ff075e255
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_20.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer20/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalag_splitac \
+ --output-prefix $FINAL_DIR/tokenizer20/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_21.sh b/sangraha/tok_sangraha/tok_files/tokenizer_21.sh
new file mode 100644
index 0000000000000000000000000000000000000000..e5a3f3f7c595fe58e9f750717f47e675bc903d78
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_21.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer21/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer21/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_22.sh b/sangraha/tok_sangraha/tok_files/tokenizer_22.sh
new file mode 100644
index 0000000000000000000000000000000000000000..4f8dc1dff6f69432b7fa47aefcf2daa041deb225
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_22.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer22/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitab \
+ --output-prefix $FINAL_DIR/tokenizer22/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_23.sh b/sangraha/tok_sangraha/tok_files/tokenizer_23.sh
new file mode 100644
index 0000000000000000000000000000000000000000..7fff4d37025c2aa467a940e6d3b47054a5be5d61
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_23.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer23/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalah_splitac \
+ --output-prefix $FINAL_DIR/tokenizer23/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_24.sh b/sangraha/tok_sangraha/tok_files/tokenizer_24.sh
new file mode 100644
index 0000000000000000000000000000000000000000..46e416e1834cf99ee22a096ddfcda9ad5a79ca0a
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_24.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer24/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer24/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_25.sh b/sangraha/tok_sangraha/tok_files/tokenizer_25.sh
new file mode 100644
index 0000000000000000000000000000000000000000..8787a3db4c7ca25219d6497dae1d28219d97db61
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_25.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer25/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitab \
+ --output-prefix $FINAL_DIR/tokenizer25/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_26.sh b/sangraha/tok_sangraha/tok_files/tokenizer_26.sh
new file mode 100644
index 0000000000000000000000000000000000000000..497d66f775724f4285e54003ef43ad6a86a12f2e
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_26.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer26/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalai_splitac \
+ --output-prefix $FINAL_DIR/tokenizer26/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_27.sh b/sangraha/tok_sangraha/tok_files/tokenizer_27.sh
new file mode 100644
index 0000000000000000000000000000000000000000..57daa6af115fae05194adab6976fd01044851cb3
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_27.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer27/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer27/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_28.sh b/sangraha/tok_sangraha/tok_files/tokenizer_28.sh
new file mode 100644
index 0000000000000000000000000000000000000000..3b22ae9008e213bafb03b73ba3d4032cdf775235
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_28.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer28/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitab \
+ --output-prefix $FINAL_DIR/tokenizer28/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_29.sh b/sangraha/tok_sangraha/tok_files/tokenizer_29.sh
new file mode 100644
index 0000000000000000000000000000000000000000..af67a043d698d3017d73f8d22f0f2b20245d191c
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_29.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer29/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalaj_splitac \
+ --output-prefix $FINAL_DIR/tokenizer29/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_3.sh b/sangraha/tok_sangraha/tok_files/tokenizer_3.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9d0c2e0b4628ed830a4cf31e937abb076db3e312
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_3.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer3/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer3/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_30.sh b/sangraha/tok_sangraha/tok_files/tokenizer_30.sh
new file mode 100644
index 0000000000000000000000000000000000000000..e0fdada8e42ef135ed6c18c07c7a6068020ae431
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_30.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer30/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer30/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_31.sh b/sangraha/tok_sangraha/tok_files/tokenizer_31.sh
new file mode 100644
index 0000000000000000000000000000000000000000..53835f4cfe793bc9296ba6570a28172eda9378f4
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_31.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer31/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitab \
+ --output-prefix $FINAL_DIR/tokenizer31/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_32.sh b/sangraha/tok_sangraha/tok_files/tokenizer_32.sh
new file mode 100644
index 0000000000000000000000000000000000000000..26e98735bcbcf6ea55b03fbaf4178e18bb83ccb7
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_32.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer32/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalak_splitac \
+ --output-prefix $FINAL_DIR/tokenizer32/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_33.sh b/sangraha/tok_sangraha/tok_files/tokenizer_33.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5810183c62670881748344c122a1f57037f23c1e
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_33.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer33/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer33/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_34.sh b/sangraha/tok_sangraha/tok_files/tokenizer_34.sh
new file mode 100644
index 0000000000000000000000000000000000000000..96831fbf5fac8d3c3f1639fd8bc38f04c0ab01c4
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_34.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer34/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitab \
+ --output-prefix $FINAL_DIR/tokenizer34/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_35.sh b/sangraha/tok_sangraha/tok_files/tokenizer_35.sh
new file mode 100644
index 0000000000000000000000000000000000000000..535b9544b03f93623b07e4cc60f1681699dd42d9
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_35.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer35/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalal_splitac \
+ --output-prefix $FINAL_DIR/tokenizer35/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_36.sh b/sangraha/tok_sangraha/tok_files/tokenizer_36.sh
new file mode 100644
index 0000000000000000000000000000000000000000..0ee60915c8e249783233f339d3bf8151ff82438a
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_36.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer36/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer36/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_37.sh b/sangraha/tok_sangraha/tok_files/tokenizer_37.sh
new file mode 100644
index 0000000000000000000000000000000000000000..c27fe1a883e6b40b84467ef7c13adbcfe3981a00
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_37.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer37/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitab \
+ --output-prefix $FINAL_DIR/tokenizer37/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_38.sh b/sangraha/tok_sangraha/tok_files/tokenizer_38.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9ba0455bfff4d429436dfd6ce794f829d90593c4
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_38.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer38/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalam_splitac \
+ --output-prefix $FINAL_DIR/tokenizer38/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_39.sh b/sangraha/tok_sangraha/tok_files/tokenizer_39.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9410cccbfd32bb8dd60cdbcd34dfae7b276d0898
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_39.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer39/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer39/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_4.sh b/sangraha/tok_sangraha/tok_files/tokenizer_4.sh
new file mode 100644
index 0000000000000000000000000000000000000000..58d1ba7f432247304c40aabc56752a287fb12c66
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_4.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer4/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitab \
+ --output-prefix $FINAL_DIR/tokenizer4/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_40.sh b/sangraha/tok_sangraha/tok_files/tokenizer_40.sh
new file mode 100644
index 0000000000000000000000000000000000000000..b1fddaa2ae4c2ff79802e263496e5d9a208a03e4
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_40.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer40/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitab \
+ --output-prefix $FINAL_DIR/tokenizer40/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_41.sh b/sangraha/tok_sangraha/tok_files/tokenizer_41.sh
new file mode 100644
index 0000000000000000000000000000000000000000..83e6b46c3cb5ddf062407be68ec0b2fc2af8ef98
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_41.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer41/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalan_splitac \
+ --output-prefix $FINAL_DIR/tokenizer41/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_42.sh b/sangraha/tok_sangraha/tok_files/tokenizer_42.sh
new file mode 100644
index 0000000000000000000000000000000000000000..ed6eda1d215bc44e51b2839f25d19f85ea8b3416
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_42.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer42/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer42/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_43.sh b/sangraha/tok_sangraha/tok_files/tokenizer_43.sh
new file mode 100644
index 0000000000000000000000000000000000000000..cb73a8002821617d7716b96d69f8c5af669f0c4c
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_43.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer43/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitab \
+ --output-prefix $FINAL_DIR/tokenizer43/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_44.sh b/sangraha/tok_sangraha/tok_files/tokenizer_44.sh
new file mode 100644
index 0000000000000000000000000000000000000000..327fe3adb9f355d8a0ee61d4d2e020889cf8b124
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_44.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer44/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalao_splitac \
+ --output-prefix $FINAL_DIR/tokenizer44/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_45.sh b/sangraha/tok_sangraha/tok_files/tokenizer_45.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9ca83f684d9e3a30f0d3a05d5ea2f7d5f21436c5
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_45.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalap
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer45/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalap \
+ --output-prefix $FINAL_DIR/tokenizer45/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_5.sh b/sangraha/tok_sangraha/tok_files/tokenizer_5.sh
new file mode 100644
index 0000000000000000000000000000000000000000..643980692cc8005f491745374bfb80ba807c1677
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_5.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer5/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalab_splitac \
+ --output-prefix $FINAL_DIR/tokenizer5/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_6.sh b/sangraha/tok_sangraha/tok_files/tokenizer_6.sh
new file mode 100644
index 0000000000000000000000000000000000000000..3c3750a0249e5e1b557ceb4d0f3a7b265d07c6d9
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_6.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer6/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer6/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_7.sh b/sangraha/tok_sangraha/tok_files/tokenizer_7.sh
new file mode 100644
index 0000000000000000000000000000000000000000..b81e6611818080dc8978bcbc0b32f550308f0f3d
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_7.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer7/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitab \
+ --output-prefix $FINAL_DIR/tokenizer7/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_8.sh b/sangraha/tok_sangraha/tok_files/tokenizer_8.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5fc81d987c82c1c0d8f43295b5caf8623eadcad1
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_8.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer8/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalac_splitac \
+ --output-prefix $FINAL_DIR/tokenizer8/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_files/tokenizer_9.sh b/sangraha/tok_sangraha/tok_files/tokenizer_9.sh
new file mode 100644
index 0000000000000000000000000000000000000000..cfd9c45de2777ca4ed69f67886a2b3e539036f84
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_files/tokenizer_9.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/peacock-data/idc/sangraha/sangraha/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k/
+TOKENIZER=$TOKENIZER_PATH/all.model
+VOCAB_FILE=$TOKENIZER_PATH/all.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer9/
+cd /mnt/weka/peacock/training/llama3b/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/split//finalad_splitaa \
+ --output-prefix $FINAL_DIR/tokenizer9/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_20.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_20.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..17b0f37a34e6c701825144ab3fb1202c62e7e17a
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_20.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-20
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_20.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_21.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_21.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..68b52f07afea14af5221a3f7f50ec44ea4bd9431
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_21.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-21
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_21.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_22.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_22.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..bf58f72639fd81ef55f93dbeaa33e7615640e480
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_22.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-22
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_22.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_23.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_23.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..76919084b2760651650b8d84315ce149c3f1b316
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_23.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-23
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_23.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_24.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_24.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d41e9cdd0ad81c5de572ce973150903acc819713
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_24.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-24
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_24.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_25.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_25.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..55359758d680c30f86558e5ff1e9e338383c119c
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_25.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-25
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_25.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_26.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_26.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..557ff8280eabcd1d1d74b190bf4a2ae95cb9ab6d
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_26.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-26
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_26.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_27.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_27.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d882c955316cb68579030e7086e3d60c72114715
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_27.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-27
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_27.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_28.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_28.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e8391d2d9187dcdeb99cdf6f7fbe96af9db23617
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_28.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-28
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_28.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs2/tokenizer_29.yaml b/sangraha/tok_sangraha/tok_jobs2/tokenizer_29.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..472fc4dca51559786e659f829375e91863933ac8
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs2/tokenizer_29.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-29
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_29.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_31.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_31.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..cddedd2c2f58e2ff467b8b067a0110ab4d4028a6
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_31.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-31
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_31.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_32.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_32.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e0c42bfd2f620093f14a1507661e7817093535ed
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_32.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-32
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_32.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_33.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_33.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..66212dfd602d22f72944f61675939ebf4b354480
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_33.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-33
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_33.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_34.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_34.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0aaa4e4320d279f006e0a16ad1b95a0f1f506ccd
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_34.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-34
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_34.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_36.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_36.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5c89f2464aa44be011b232f84be6e39774d1a2c2
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_36.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-36
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_36.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_38.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_38.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c3b61fc532f697636fad74adfad7a42973f4768b
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_38.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-38
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_38.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+                    
diff --git a/sangraha/tok_sangraha/tok_jobs3/tokenizer_39.yaml b/sangraha/tok_sangraha/tok_jobs3/tokenizer_39.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..faadfb00f3f113a2f426a1b90e5e3e3e26609a48
--- /dev/null
+++ b/sangraha/tok_sangraha/tok_jobs3/tokenizer_39.yaml
@@ -0,0 +1,122 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-sangraha-39
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 0
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  sleep 10;
+                  export SYNAPSE_VERSION="1.17.0";
+                  export WORKER_DIR="/mnt/weka/peacock/training/llama3b";
+                  export MODEL_PATH="${WORKER_DIR}/Megatron-DeepSpeed";
+                  export MEGATRON_DEEPSPEED_ROOT=$MODEL_PATH;
+                  export MODEL_REQ="${MODEL_PATH}/megatron/core/requirements.txt";
+
+                  export TOKENIZER_CMD=/mnt/weka/peacock/peacock-data/idc/datasets/sangraha//tok_sangraha/tok_files/tokenizer_39.sh
+
+                  export HL_LLAMA_VER=2;
+                  export HL_LLAMA_MODEL_SIZE=3;
+
+                  export HL_DATA_DIR_ROOT="/mnt/weka/peacock/peacock-data/idc/hineng/hn_eng_bn/merged_all";
+                  export HL_DATA_FILE_PREFIX="all";
+                  export HL_DATASET_NAME=slimpajama-subset;
+                  export HL_DP=16;
+                  export HL_PP=2;
+                  export HL_TP=4;
+                  export HL_TRAIN_ITERS=240000;
+                  export HL_SAVE_INTERVAL=1000;
+
+                  #export HL_EXIT_INTERVAL=100;
+                  #export HL_SAVE=0;
+
+                  export HL_MICRO_BATCH=8;
+
+                  export HL_TOKENIZER_TYPE=SentencePieceTokenizer;
+                  export HL_TOKENIZER_DIR="/mnt/weka/peacock/peacock-data/tokenization/trained-tokenizer/enhiben_50k";
+
+                  export RESULT_DESCRIPTION="${HL_DATASET_NAME}-TI${HL_TRAIN_ITERS}-TP${HL_TP}PP${HL_PP}DP${HL_DP}-MBS${HL_MICRO_BATCH}";
+                  export DEBUG=True;
+
+                  set -exo pipefail; 
+
+
+                  $WORKER_DIR/launch/setup.sh;
+
+                  mpirun  --npernode 1 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x MODEL_REQ=$MODEL_REQ \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x MODEL_PATH=$MODEL_PATH \
+                    -x MODEL_REFERENCES_ROOT=$MODEL_REFERENCES_ROOT \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION \
+                    $WORKER_DIR/launch/setup.sh;
+
+                  cd $MODEL_PATH;
+
+                  mpirun  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          runtimeClassName: habana
+          nodeSelector:
+            role: worker
+          volumes:
+            - name: pvc-wekafs-peacock
+              persistentVolumeClaim:
+                claimName: pvc-wekafs-peacock
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest
+              name: llama2-3b-pretrain-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 600Gi
+                  cpu: 120
+              volumeMounts:
+                - name: pvc-wekafs-peacock
+                  mountPath: /mnt/weka/peacock
+