diff --git a/lm-evaluation/lm_eval/tasks/belebele/_default_template_yaml b/lm-evaluation/lm_eval/tasks/belebele/_default_template_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2583ced5688e1a0f97f3c46b1bc64d54c329a172
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/_default_template_yaml
@@ -0,0 +1,19 @@
+group: belebele
+dataset_path: facebook/belebele
+fewshot_config:
+  sampler: first_n
+output_type: multiple_choice
+should_decontaminate: true
+doc_to_decontamination_query: "{{question}}"
+doc_to_text: "P: {{flores_passage}}\nQ: {{question.strip()}}\nA: {{mc_answer1}}\nB: {{mc_answer2}}\nC: {{mc_answer3}}\nD: {{mc_answer4}}\nAnswer："
+doc_to_choice: ["A", "B", "C", "D"]
+doc_to_target: "{{['1', '2', '3', '4'].index(correct_answer_num)}}"
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true
+  - metric: acc_norm
+    aggregation: mean
+    higher_is_better: true
+metadata:
+  version: 0.0
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_amh_Ethi.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_amh_Ethi.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e3d61066cf9ccdce81c9c5b91682c1616cc28e6a
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_amh_Ethi.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "amh_Ethi"
+"include": "_default_template_yaml"
+"task": "belebele_amh_Ethi"
+"test_split": "amh_Ethi"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_arb_Arab.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_arb_Arab.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b6242fd38b2666f496751b8ed03639f712f350e3
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_arb_Arab.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "arb_Arab"
+"include": "_default_template_yaml"
+"task": "belebele_arb_Arab"
+"test_split": "arb_Arab"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_asm_Beng.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_asm_Beng.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c24a1deceac5c596705e95c03e43b327363be9ae
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_asm_Beng.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "asm_Beng"
+"include": "_default_template_yaml"
+"task": "belebele_asm_Beng"
+"test_split": "asm_Beng"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_ben_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_ben_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c8736c5242e5b8ff3f717c317292a42fd718db5b
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_ben_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "ben_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_ben_Latn"
+"test_split": "ben_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_est_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_est_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6a56ca90c0309d9475adad9b95db272577658f36
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_est_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "est_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_est_Latn"
+"test_split": "est_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_fuv_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_fuv_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2636cae850c6222906fac7f3c1533ea16684ee73
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_fuv_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "fuv_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_fuv_Latn"
+"test_split": "fuv_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_hin_Deva.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_hin_Deva.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9fa304c9b09100d17edd37a5f7caa1b11f5d22df
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_hin_Deva.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "hin_Deva"
+"include": "_default_template_yaml"
+"task": "belebele_hin_Deva"
+"test_split": "hin_Deva"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_ilo_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_ilo_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fc3065da1c1a8c968845910a6f330c262a6a8a8e
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_ilo_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "ilo_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_ilo_Latn"
+"test_split": "ilo_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_ind_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_ind_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c15fff3ec36a0b3b140581f317553b2fa0e2e62c
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_ind_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "ind_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_ind_Latn"
+"test_split": "ind_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_isl_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_isl_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..69f9bb4e372ce1a39057ce4b70a7e48d23d199e2
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_isl_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "isl_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_isl_Latn"
+"test_split": "isl_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_jpn_Jpan.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_jpn_Jpan.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..73b60502bc90b9e2128f9e2eb72046cf961b1054
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_jpn_Jpan.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "jpn_Jpan"
+"include": "_default_template_yaml"
+"task": "belebele_jpn_Jpan"
+"test_split": "jpn_Jpan"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_kac_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_kac_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..002bc9a15882eb9f51f745baa79cd22313ea92aa
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_kac_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "kac_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_kac_Latn"
+"test_split": "kac_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_kat_Geor.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_kat_Geor.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6392d29bbe98cf3c6e228d20c90dbb7cf1281789
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_kat_Geor.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "kat_Geor"
+"include": "_default_template_yaml"
+"task": "belebele_kat_Geor"
+"test_split": "kat_Geor"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_khm_Khmr.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_khm_Khmr.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..39641c836b4ccf13ff16a730ef0ddd0ed6cc0962
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_khm_Khmr.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "khm_Khmr"
+"include": "_default_template_yaml"
+"task": "belebele_khm_Khmr"
+"test_split": "khm_Khmr"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_lug_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_lug_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3de4c1cd96efadff9245b077b1d5cfca78a8e292
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_lug_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "lug_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_lug_Latn"
+"test_split": "lug_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_mkd_Cyrl.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_mkd_Cyrl.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c9887108a949eae7be2e17e28a7ed9f81559f303
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_mkd_Cyrl.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "mkd_Cyrl"
+"include": "_default_template_yaml"
+"task": "belebele_mkd_Cyrl"
+"test_split": "mkd_Cyrl"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_mri_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_mri_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d704cdc478175da6c8894a08da2d2e177f895ed2
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_mri_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "mri_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_mri_Latn"
+"test_split": "mri_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_nld_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_nld_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..aea069996198c6bad23ed44969d3bc840ad04442
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_nld_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "nld_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_nld_Latn"
+"test_split": "nld_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_nob_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_nob_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..cf824f3b9de3ce40db37060d2348c4a7b60a4c00
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_nob_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "nob_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_nob_Latn"
+"test_split": "nob_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_npi_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_npi_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e2ff68ad9a17c247ec2c8a9df996df7dbb9e115a
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_npi_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "npi_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_npi_Latn"
+"test_split": "npi_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_pes_Arab.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_pes_Arab.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ceda24e2a9be857e76584dff421da71427f6c50e
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_pes_Arab.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "pes_Arab"
+"include": "_default_template_yaml"
+"task": "belebele_pes_Arab"
+"test_split": "pes_Arab"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_plt_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_plt_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..17889ae3556278624d79fe9bc632310a3008c66c
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_plt_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "plt_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_plt_Latn"
+"test_split": "plt_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_pol_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_pol_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ebfcf3534e53c10bfe370643bfc50fc94df5602c
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_pol_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "pol_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_pol_Latn"
+"test_split": "pol_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_por_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_por_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f63ace02d5a3fb8cc1b0b85a279c49370567b16c
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_por_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "por_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_por_Latn"
+"test_split": "por_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_ron_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_ron_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ab1ad0889b4797ce6068fd1c8741fc45e29cb588
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_ron_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "ron_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_ron_Latn"
+"test_split": "ron_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_rus_Cyrl.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_rus_Cyrl.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..280768c7c61d44a0a9e7bb8aeae64ebbecfdd84a
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_rus_Cyrl.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "rus_Cyrl"
+"include": "_default_template_yaml"
+"task": "belebele_rus_Cyrl"
+"test_split": "rus_Cyrl"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_shn_Mymr.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_shn_Mymr.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..75bbd05b16c54b593729f9a8f7b4499c25d2f5ed
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_shn_Mymr.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "shn_Mymr"
+"include": "_default_template_yaml"
+"task": "belebele_shn_Mymr"
+"test_split": "shn_Mymr"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_slk_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_slk_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..cddd1eb1e67713b5c635e598ece58d115dc0b4c0
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_slk_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "slk_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_slk_Latn"
+"test_split": "slk_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_slv_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_slv_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9e3e5338231b478c0c9614dabb6e26c7dd11d994
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_slv_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "slv_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_slv_Latn"
+"test_split": "slv_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_som_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_som_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fa1d4329d878e141ffbbb3f7faed774abbfccacb
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_som_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "som_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_som_Latn"
+"test_split": "som_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_swe_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_swe_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6ac7a4afffb3db57119df0db971415e48aa94301
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_swe_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "swe_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_swe_Latn"
+"test_split": "swe_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_tel_Telu.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_tel_Telu.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..de44fcc4848927331994d5ca42dce064c7758483
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_tel_Telu.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "tel_Telu"
+"include": "_default_template_yaml"
+"task": "belebele_tel_Telu"
+"test_split": "tel_Telu"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_tsn_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_tsn_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e9c7aa83cf7f4195ad3f113f1420046d8986ed8a
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_tsn_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "tsn_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_tsn_Latn"
+"test_split": "tsn_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_uzn_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_uzn_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..109aebdd5fc3c6a07083821dae0f61c0037b6ae2
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_uzn_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "uzn_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_uzn_Latn"
+"test_split": "uzn_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_yor_Latn.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_yor_Latn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9eb295cc0471885c83a4114b0551d134611d8c56
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_yor_Latn.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "yor_Latn"
+"include": "_default_template_yaml"
+"task": "belebele_yor_Latn"
+"test_split": "yor_Latn"
diff --git a/lm-evaluation/lm_eval/tasks/belebele/belebele_zho_Hans.yaml b/lm-evaluation/lm_eval/tasks/belebele/belebele_zho_Hans.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..32b0860bdaa2806161c32d9d8359d02ec61140d2
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/belebele/belebele_zho_Hans.yaml
@@ -0,0 +1,4 @@
+"fewshot_split": "zho_Hans"
+"include": "_default_template_yaml"
+"task": "belebele_zho_Hans"
+"test_split": "zho_Hans"
diff --git a/lm-evaluation/lm_eval/tasks/eus_trivia/README.md b/lm-evaluation/lm_eval/tasks/eus_trivia/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..88e760e43592d93ba27ee3b19c4edd0fc6f3e9f6
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/eus_trivia/README.md
@@ -0,0 +1,54 @@
+# EusTrivia
+
+### Paper
+
+Title: Latxa: An Open Language Model and Evaluation Suite for Basque
+
+Abstract: https://arxiv.org/abs/2403.20266
+
+EusTrivia consists of 1,715 trivia questions from multiple online sources. 56.3\% of the questions are elementary level (grades 3-6), while the rest are considered challenging. A significant portion of the questions focus specifically on the Basque Country, its language and culture. Each multiple-choice question contains two, three or four choices (3.84 on average) and a single correct answer. Five areas of knowledge are covered:
+
+- **Humanities and Natural Sciences** (27.8%): This category encompasses questions about history, geography, biology, ecology and other social and natural sciences.
+- **Leisure and Art** (24.5%): This category includes questions on sports and athletes, performative and plastic arts and artists, architecture, cultural events, and related topics.
+- **Music** (16.0%): Here are grouped all the questions about music and musicians, both classical and contemporary.
+- **Language and Literature** (17.1%): This category is concerned with all kinds of literature productions and writers, as well as metalinguistic questions (e.g., definitions, synonyms, and word usage).
+- **Mathematics and ICT** (14.5%): This category covers mathematical problems and questions about ICT, as well as questions about people known for their contributions to these fields of knowledge.
+
+Homepage: https://github.com/hitz-zentroa/latxa
+
+
+### Citation
+
+```
+@misc{etxaniz2024latxa,
+      title={Latxa: An Open Language Model and Evaluation Suite for Basque},
+      author={Julen Etxaniz and Oscar Sainz and Naiara Perez and Itziar Aldabe and German Rigau and Eneko Agirre and Aitor Ormazabal and Mikel Artetxe and Aitor Soroa},
+      year={2024},
+      eprint={2403.20266},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+### Groups and Tasks
+
+#### Groups
+
+There are no groups.
+
+#### Tasks
+
+* `eus_trivia`: EusTrivia consists of 1,715 trivia questions from multiple online sources.
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+* [ ] Is the task an existing benchmark in the literature?
+  * [ ] Have you referenced the original paper that introduced the task?
+  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+
+If other tasks on this dataset are already supported:
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
diff --git a/lm-evaluation/lm_eval/tasks/eus_trivia/eus_trivia.yaml b/lm-evaluation/lm_eval/tasks/eus_trivia/eus_trivia.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fe93ab61725867ae39d9be17ae33f9b769046683
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/eus_trivia/eus_trivia.yaml
@@ -0,0 +1,16 @@
+dataset_path: HiTZ/EusTrivia
+dataset_name: default
+task: eus_trivia
+doc_to_text: !function utils.doc_to_text
+doc_to_choice: !function utils.doc_to_choice
+validation_split: null
+test_split: test
+fewshot_split: test
+output_type: multiple_choice
+doc_to_target: answer
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true
+metadata:
+  version: 0.0
diff --git a/lm-evaluation/lm_eval/tasks/eus_trivia/utils.py b/lm-evaluation/lm_eval/tasks/eus_trivia/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..e5802c795bf558eacb60a05db6c344e925f6e4fa
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/eus_trivia/utils.py
@@ -0,0 +1,41 @@
+from typing import List
+
+
+letters = ["A", "B", "C", "D"]
+
+
+def doc_to_text(doc) -> str:
+    """
+    Converts a document to a formatted string.
+
+    Args:
+        doc (dict): A dictionary containing the document information.
+
+    Returns:
+        str: A formatted string containing the question and answer choices.
+    """
+    candidates = doc["candidates"]
+    num_choices = len(candidates)
+    if num_choices < 2:
+        raise ValueError("Invalid number of candidates")
+    choices = letters[:num_choices]
+    formatted_choices = "\n".join(
+        [f"{choice}: {candidates[i]}" for i, choice in enumerate(choices)]
+    )
+    return f"Galdera: {doc['question']}\n{formatted_choices}\nErantzuna:"
+
+
+def doc_to_choice(doc) -> List[str]:
+    """
+    Returns the answer choices for a document.
+
+    Args:
+        doc (dict): A dictionary containing the document information.
+
+    Returns:
+        list: A list of strings containing the answer choices.
+    """
+    num_choices = len(doc["candidates"])
+    if num_choices < 2:
+        raise ValueError("Invalid number of candidates")
+    return letters[:num_choices]
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/_gpqa_cot_n_shot_yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/_gpqa_cot_n_shot_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..193539b92001223df8052167624d94e0c997d2cd
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/_gpqa_cot_n_shot_yaml
@@ -0,0 +1,38 @@
+dataset_path: Idavidrein/gpqa
+group: gpqa
+output_type: generate_until
+process_docs: !function utils.process_docs
+training_split: train
+# Because huggingface dataset only has train split
+validation_split: train
+test_split: null
+description: "Here are some example questions from experts. Answer the final question yourself, following the format of the previous questions exactly.\n"
+doc_to_text: "Question: {{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nLet's think step by step: "
+doc_to_target: answer
+filter_list:
+  - name: "strict-match"
+    filter:
+      - function: "regex"
+        regex_pattern: "(?<=The answer is )(.*)(?=.)"
+      - function: "take_first"
+  - name: "flexible-extract"
+    filter:
+      - function: "multi_choice_regex"
+        group_select: -1
+        ignore_case: true
+        ignore_punctuation: true
+        regex_pattern: "(\\([A-Z]\\))"
+      - function: "take_first"
+generation_kwargs:
+  until:
+    - "</s>"
+  do_sample: false
+  temperature: 0.0
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+    ignore_case: true
+    ignore_punctuation: true
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/gpqa_main_cot_n_shot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/gpqa_main_cot_n_shot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..916b6ea06a2e22042344b668191adbb3c91c4e75
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_n_shot/gpqa_main_cot_n_shot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_main
+include: _gpqa_cot_n_shot_yaml
+task: gpqa_main_cot_n_shot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_generate_configs.py b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_generate_configs.py
new file mode 100644
index 0000000000000000000000000000000000000000..bda00784cc2fa26b5f0d488cf7b6aea37243353d
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_generate_configs.py
@@ -0,0 +1,26 @@
+import yaml
+from tqdm import tqdm
+
+
+def main() -> None:
+    subset = ["extended", "diamond", "main"]
+    setting = "cot_zeroshot"
+    for task in tqdm(subset):
+        file_name = f"gpqa_{task}_{setting}.yaml"
+        try:
+            with open(f"{file_name}", "w") as f:
+                f.write("# Generated by _generate_configs.py\n")
+                yaml.dump(
+                    {
+                        "include": f"_gpqa_{setting}_yaml",
+                        "task": f"gpqa_{task}_{setting}",
+                        "dataset_name": f"gpqa_{task}",
+                    },
+                    f,
+                )
+        except FileExistsError:
+            pass
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_gpqa_cot_zeroshot_yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_gpqa_cot_zeroshot_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..df99f272c99a343d4250c44e3618f85e9e2a0682
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/_gpqa_cot_zeroshot_yaml
@@ -0,0 +1,38 @@
+dataset_path: Idavidrein/gpqa
+group: gpqa
+output_type: generate_until
+process_docs: !function utils.process_docs
+training_split: train
+# Because huggingface dataset only has train split
+validation_split: train
+test_split: null
+doc_to_text: "What is the correct answer to this question:{{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nLet's think step by step: "
+doc_to_target: answer
+filter_list:
+  - name: "strict-match"
+    filter:
+      - function: "regex"
+        regex_pattern: "(?<=The answer is )(.*)(?=.)"
+      - function: "take_first"
+  - name: "flexible-extract"
+    filter:
+      - function: "multi_choice_regex"
+        group_select: -1
+        ignore_case: true
+        ignore_punctuation: true
+        regex_pattern: "(\\([A-Z]\\))"
+      - function: "take_first"
+generation_kwargs:
+  until:
+    - "</s>"
+  do_sample: false
+  temperature: 0.0
+num_fewshot: 0
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+    ignore_case: true
+    ignore_punctuation: true
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_diamond_cot_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_diamond_cot_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e6a840fa1815096f5fa180ed06223e3523a06214
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_diamond_cot_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_diamond
+include: _gpqa_cot_zeroshot_yaml
+task: gpqa_diamond_cot_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_extended_cot_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_extended_cot_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9f542a6148f231e2d7e7e2a5a3437047459e3856
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_extended_cot_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_extended
+include: _gpqa_cot_zeroshot_yaml
+task: gpqa_extended_cot_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_main_cot_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_main_cot_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8c14604854294c4551e2602e573488c6a7fef254
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/gpqa_main_cot_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_main
+include: _gpqa_cot_zeroshot_yaml
+task: gpqa_main_cot_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/utils.py b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..96bcd52b140fd0a5896f55c0a52ea2fd5453fd53
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/cot_zeroshot/utils.py
@@ -0,0 +1,39 @@
+import random
+import re
+
+import datasets
+
+
+def preprocess(text):
+    if text is None:
+        return " "
+    text = text.strip()
+    text = text.replace(" [title]", ". ")
+    text = re.sub("\\[.*?\\]", "", text)
+    text = text.replace("  ", " ")
+    return text
+
+
+def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:
+    def _process_doc(doc):
+        choices = [
+            preprocess(doc["Incorrect Answer 1"]),
+            preprocess(doc["Incorrect Answer 2"]),
+            preprocess(doc["Incorrect Answer 3"]),
+            preprocess(doc["Correct Answer"]),
+        ]
+
+        random.shuffle(choices)
+        correct_answer_index = choices.index(preprocess(doc["Correct Answer"]))
+
+        out_doc = {
+            "choice1": choices[0],
+            "choice2": choices[1],
+            "choice3": choices[2],
+            "choice4": choices[3],
+            "choices": [choices[0], choices[1], choices[2], choices[3]],
+            "answer": f"({chr(65 + correct_answer_index)})",
+        }
+        return out_doc
+
+    return dataset.map(_process_doc)
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_generate_configs.py b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_generate_configs.py
new file mode 100644
index 0000000000000000000000000000000000000000..c01f208e767cb813e6d2116caf74c3d0b2fccfb3
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_generate_configs.py
@@ -0,0 +1,26 @@
+import yaml
+from tqdm import tqdm
+
+
+def main() -> None:
+    subset = ["extended", "diamond", "main"]
+
+    for task in tqdm(subset):
+        file_name = f"gpqa_{task}_n_shot.yaml"
+        try:
+            with open(f"{file_name}", "w") as f:
+                f.write("# Generated by _generate_configs.py\n")
+                yaml.dump(
+                    {
+                        "include": "_gpqa_n_shot_yaml",
+                        "task": f"gpqa_{task}_n_shot",
+                        "dataset_name": f"gpqa_{task}",
+                    },
+                    f,
+                )
+        except FileExistsError:
+            pass
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_gpqa_n_shot_yaml b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_gpqa_n_shot_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..96d4fc25ff1360e3ff989961230383a2de59b7eb
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/_gpqa_n_shot_yaml
@@ -0,0 +1,21 @@
+dataset_path: Idavidrein/gpqa
+group: gpqa
+output_type: multiple_choice
+process_docs: !function utils.process_docs
+training_split: train
+# Because huggingface dataset only has train split
+validation_split: train
+test_split: null
+description: "Here are some example questions from experts. Answer the final question yourself, following the format of the previous questions exactly.\n"
+doc_to_text: "Question: {{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nAnswer:"
+doc_to_target: answer
+doc_to_choice: ["(A)", "(B)", "(C)", "(D)"]
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true
+  - metric: acc_norm
+    aggregation: mean
+    higher_is_better: true
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_diamond_n_shot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_diamond_n_shot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3043a7e53647ff72d535abc113dfccebaa1bd43c
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_diamond_n_shot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_diamond
+include: _gpqa_n_shot_yaml
+task: gpqa_diamond_n_shot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_extended_n_shot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_extended_n_shot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5d16b505b355bccb3d6fd70eb16b307c12d06a09
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_extended_n_shot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_extended
+include: _gpqa_n_shot_yaml
+task: gpqa_extended_n_shot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_main_n_shot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_main_n_shot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7e5f3e9532ab41c0158409e6afb47393806c4177
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/gpqa_main_n_shot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_main
+include: _gpqa_n_shot_yaml
+task: gpqa_main_n_shot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/n_shot/utils.py b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..e0b886d2879216094214ce534438e4db0c5e60f8
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/n_shot/utils.py
@@ -0,0 +1,41 @@
+import random
+import re
+
+import datasets
+
+
+def preprocess(text):
+    if text is None:
+        return " "
+    text = text.strip()
+    text = text.replace(" [title]", ". ")
+    text = re.sub("\\[.*?\\]", "", text)
+    text = text.replace("  ", " ")
+    return text
+
+
+rng = random.Random(42)
+
+
+def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:
+    def _process_doc(doc):
+        choices = [
+            preprocess(doc["Incorrect Answer 1"]),
+            preprocess(doc["Incorrect Answer 2"]),
+            preprocess(doc["Incorrect Answer 3"]),
+            preprocess(doc["Correct Answer"]),
+        ]
+
+        rng.shuffle(choices)
+        correct_answer_index = choices.index(preprocess(doc["Correct Answer"]))
+
+        out_doc = {
+            "choice1": choices[0],
+            "choice2": choices[1],
+            "choice3": choices[2],
+            "choice4": choices[3],
+            "answer": f"({chr(65 + correct_answer_index)})",
+        }
+        return out_doc
+
+    return dataset.map(_process_doc)
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_generate_configs.py b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_generate_configs.py
new file mode 100644
index 0000000000000000000000000000000000000000..79afbd6f1d8d4b2eb54455d734f6245357580bd3
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_generate_configs.py
@@ -0,0 +1,26 @@
+import yaml
+from tqdm import tqdm
+
+
+def main() -> None:
+    subset = ["extended", "diamond", "main"]
+    setting = "zeroshot"
+    for task in tqdm(subset):
+        file_name = f"gpqa_{task}_{setting}.yaml"
+        try:
+            with open(f"{file_name}", "w") as f:
+                f.write("# Generated by _generate_configs.py\n")
+                yaml.dump(
+                    {
+                        "include": f"_gpqa_{setting}_yaml",
+                        "task": f"gpqa_{task}_{setting}",
+                        "dataset_name": f"gpqa_{task}",
+                    },
+                    f,
+                )
+        except FileExistsError:
+            pass
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_gpqa_zeroshot_yaml b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_gpqa_zeroshot_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..707641b5f0c6243d48f77c6a4a56d5ec824baa4e
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/_gpqa_zeroshot_yaml
@@ -0,0 +1,21 @@
+dataset_path: Idavidrein/gpqa
+group: gpqa
+output_type: multiple_choice
+process_docs: !function utils.process_docs
+training_split: train
+# Because huggingface dataset only has train split
+validation_split: train
+test_split: null
+doc_to_text: "What is the correct answer to this question:{{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nAnswer:"
+doc_to_target: answer
+doc_to_choice: ["(A)", "(B)", "(C)", "(D)"]
+num_fewshot: 0
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true
+  - metric: acc_norm
+    aggregation: mean
+    higher_is_better: true
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_diamond_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_diamond_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c3a7921c30b3ff09e82aacb4c0e915010f698966
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_diamond_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_diamond
+include: _gpqa_zeroshot_yaml
+task: gpqa_diamond_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_extended_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_extended_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5e7347f11154351ad4560200a3f3bf54106a1a8f
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_extended_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_extended
+include: _gpqa_zeroshot_yaml
+task: gpqa_extended_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_main_zeroshot.yaml b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_main_zeroshot.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1a8d7fb59025d148130f2a468cb1bbdfad959102
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/gpqa_main_zeroshot.yaml
@@ -0,0 +1,4 @@
+# Generated by _generate_configs.py
+dataset_name: gpqa_main
+include: _gpqa_zeroshot_yaml
+task: gpqa_main_zeroshot
diff --git a/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/utils.py b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..c2317e02efd132aea27ec8c8fad284df55ccd382
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/gpqa/zeroshot/utils.py
@@ -0,0 +1,38 @@
+import random
+import re
+
+import datasets
+
+
+def preprocess(text):
+    if text is None:
+        return " "
+    text = text.strip()
+    text = text.replace(" [title]", ". ")
+    text = re.sub("\\[.*?\\]", "", text)
+    text = text.replace("  ", " ")
+    return text
+
+
+def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:
+    def _process_doc(doc):
+        choices = [
+            preprocess(doc["Incorrect Answer 1"]),
+            preprocess(doc["Incorrect Answer 2"]),
+            preprocess(doc["Incorrect Answer 3"]),
+            preprocess(doc["Correct Answer"]),
+        ]
+
+        random.shuffle(choices)
+        correct_answer_index = choices.index(preprocess(doc["Correct Answer"]))
+
+        out_doc = {
+            "choice1": choices[0],
+            "choice2": choices[1],
+            "choice3": choices[2],
+            "choice4": choices[3],
+            "answer": f"({chr(65 + correct_answer_index)})",
+        }
+        return out_doc
+
+    return dataset.map(_process_doc)
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/__pycache__/utils.cpython-310.pyc b/lm-evaluation/lm_eval/tasks/indiccopa/__pycache__/utils.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..f50474f8f794d42b4b83ac620126f0d73bc5f606
Binary files /dev/null and b/lm-evaluation/lm_eval/tasks/indiccopa/__pycache__/utils.cpython-310.pyc differ
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_as.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_as.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6ac7094316356a1d29fbda640465cd59f39acff7
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_as.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-as
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_as
+
+task: indiccopa_as
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_bn.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_bn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..02bca115f39b13bc9e59ed7aa289b3af172555a0
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_bn.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-bn
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_bn
+
+task: indiccopa_bn
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_kn.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_kn.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4eff187f13f72e9510d11b3addf411f773962cbb
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_kn.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-kn
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_kn
+
+task: indiccopa_kn
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_mr.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_mr.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..bc74086dd322a6f906377a317d1767c2f882ed80
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_mr.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-mr
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_mr
+
+task: indiccopa_mr
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sa.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sa.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..044a26740ccc43a1d0c2c4c8db8baf2d72f11f25
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sa.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-sa
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_sa
+
+task: indiccopa_sa
diff --git a/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sd.yaml b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sd.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..31bf0624ff025d680a2cfcdf579ad16841c5b7fd
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indiccopa/indiccopa_sd.yaml
@@ -0,0 +1,5 @@
+dataset_name: translation-sd
+include: indiccopa_common_yaml
+doc_to_text: !function utils.doc_to_text_sd
+
+task: indiccopa_sd
diff --git a/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_common_yaml b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_common_yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a450bde02357d9b64efc47ffbd9b9634394b7287
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_common_yaml
@@ -0,0 +1,22 @@
+# This file will be included in the generated language-specific task configs.
+# It doesn't have a yaml file extension as it is not meant to be imported directly
+# by the harness.
+group: Divyanshu/indicxnli
+
+dataset_path: Divyanshu/indicxnli
+# dataset_name: null
+output_type: multiple_choice
+
+training_split: train
+validation_split: validation
+
+doc_to_text: null
+doc_to_target: label
+doc_to_choice: null
+
+metric_list:
+  - metric: acc
+    aggregation: mean
+    higher_is_better: true
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_gu.yaml b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_gu.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7e8c8cb337d95056c67941b8b743a61ab49e072b
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_gu.yaml
@@ -0,0 +1,7 @@
+# Generated by utils.py
+dataset_name: gu
+doc_to_choice: '{{[premise+", સાચું? હા, "+hypothesis,premise+", સાચું? તેનાથી, "+hypothesis,premise+",
+  સાચું? ના, "+hypothesis]}}'
+doc_to_text: ''
+include: indicxnli_common_yaml
+task: indicxnli_gu
diff --git a/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_hi.yaml b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_hi.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8897d99a6ea0b89b642ab2ddd75c11afeae42fae
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/indicxnli/indicxnli_hi.yaml
@@ -0,0 +1,7 @@
+# Generated by utils.py
+dataset_name: hi
+doc_to_choice: '{{[premise+", सही? हाँ, "+hypothesis,premise+", सही? इसलिए, "+hypothesis,premise+",
+  सही? नहीं, "+hypothesis]}}'
+doc_to_text: ''
+include: indicxnli_common_yaml
+task: indicxnli_hi
diff --git a/lm-evaluation/lm_eval/tasks/mc_taco/README.md b/lm-evaluation/lm_eval/tasks/mc_taco/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2bab6369468ecead4f3cfae9964e3a04d5e06423
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/mc_taco/README.md
@@ -0,0 +1,53 @@
+# MC Taco
+
+### Paper
+
+Title: `"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding`
+Abstract: https://arxiv.org/abs/1909.03065
+
+MC-TACO is a dataset of 13k question-answer pairs that require temporal commonsense
+comprehension. The dataset contains five temporal properties, (1) duration (how long
+an event takes), (2) temporal ordering (typical order of events), (3) typical time
+(when an event occurs), (4) frequency (how often an event occurs), and (5) stationarity
+(whether a state is maintained for a very long time or indefinitely).
+
+WARNING: Running this task with a `--limit` arg will give misleading results! The
+corresponding dataset is structured such that each multiple-choice-question gathered
+by the authors is split into question-option pairs, where each such pair gets
+siloed into an individual document for plausibility testing. Because the harness
+shuffles these documents, setting `--limit` will likely "cut off" certain candidate
+answers. This is a problem because the task's metrics require an exhaustive evaluation
+of a question's options. See section 4 of the paper for details.
+
+Homepage: https://leaderboard.allenai.org/mctaco/submissions/public
+
+
+### Citation
+
+```
+BibTeX-formatted citation goes here
+```
+
+### Groups and Tasks
+
+#### Groups
+
+* Not part of a group yet.
+
+#### Tasks
+
+* `mc_taco`
+
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+* [ ] Is the task an existing benchmark in the literature?
+  * [ ] Have you referenced the original paper that introduced the task?
+  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+
+If other tasks on this dataset are already supported:
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
diff --git a/lm-evaluation/lm_eval/tasks/mc_taco/default.yaml b/lm-evaluation/lm_eval/tasks/mc_taco/default.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..16aee3f7e76098acdd53ec88adf5cc078e3a5907
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/mc_taco/default.yaml
@@ -0,0 +1,15 @@
+task: mc_taco
+dataset_path: mc_taco
+output_type: multiple_choice
+validation_split: validation
+test_split: test
+doc_to_text: "{{sentence}}\nQuestion: {{question}}\nAnswer: {{answer}}\nPlausible:"
+doc_to_target: label
+doc_to_choice: ["no", "yes"]
+should_decontaminate: true
+doc_to_decontamination_query: "{{question}} {{sentence}}"
+metric_list:
+  - metric: acc
+  - metric: f1
+metadata:
+  version: 1.0
diff --git a/lm-evaluation/lm_eval/tasks/squadv2/README.md b/lm-evaluation/lm_eval/tasks/squadv2/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..bad0c4e2d80ec17c3f4a4c2f15db2ce6a6632db4
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/squadv2/README.md
@@ -0,0 +1,54 @@
+# Task-name
+
+### Paper
+
+Title: `Know What You Don’t Know: Unanswerable Questions for SQuAD`
+Abstract: https://arxiv.org/abs/1806.03822
+
+Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset,
+consisting of questions posed by crowdworkers on a set of Wikipedia articles,
+where the answer to every question is a segment of text, or span, from the
+corresponding reading passage, or the question might be unanswerable.
+SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable
+questions written adversarially by crowdworkers to look similar to answerable ones.
+To do well on SQuAD2.0, systems must not only answer questions when possible, but
+also determine when no answer is supported by the paragraph and abstain from answering.
+
+Homepage: https://rajpurkar.github.io/SQuAD-explorer/
+
+
+### Citation
+
+```
+@misc{rajpurkar2018know,
+    title={Know What You Don't Know: Unanswerable Questions for SQuAD},
+    author={Pranav Rajpurkar and Robin Jia and Percy Liang},
+    year={2018},
+    eprint={1806.03822},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+### Groups and Tasks
+
+#### Groups
+
+* Not part of a group yet
+
+#### Tasks
+
+* `squadv2`: `Default squadv2 task`
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+* [ ] Is the task an existing benchmark in the literature?
+  * [ ] Have you referenced the original paper that introduced the task?
+  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+
+If other tasks on this dataset are already supported:
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?
diff --git a/lm-evaluation/lm_eval/tasks/squadv2/squadv2.yaml b/lm-evaluation/lm_eval/tasks/squadv2/squadv2.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..13e451645cc23284f3b45f15527c365410118617
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/squadv2/squadv2.yaml
@@ -0,0 +1,2 @@
+task: squadv2
+class: !function task.SQuAD2
diff --git a/lm-evaluation/lm_eval/tasks/squadv2/task.py b/lm-evaluation/lm_eval/tasks/squadv2/task.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef6be3e1fe208893c19163d6dc6f9d3fba38cb8a
--- /dev/null
+++ b/lm-evaluation/lm_eval/tasks/squadv2/task.py
@@ -0,0 +1,240 @@
+"""
+Know What You Don’t Know: Unanswerable Questions for SQuAD
+https://arxiv.org/pdf/1806.03822.pdf
+
+Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset,
+consisting of questions posed by crowdworkers on a set of Wikipedia articles,
+where the answer to every question is a segment of text, or span, from the
+corresponding reading passage, or the question might be unanswerable.
+SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable
+questions written adversarially by crowdworkers to look similar to answerable ones.
+To do well on SQuAD2.0, systems must not only answer questions when possible, but
+also determine when no answer is supported by the paragraph and abstain from answering.
+
+Homepage: https://rajpurkar.github.io/SQuAD-explorer/
+"""
+from functools import partial
+from math import exp
+
+import datasets
+from packaging import version
+
+from lm_eval.api.instance import Instance
+from lm_eval.api.task import ConfigurableTask
+
+
+_CITATION = """
+@misc{rajpurkar2018know,
+    title={Know What You Don't Know: Unanswerable Questions for SQuAD},
+    author={Pranav Rajpurkar and Robin Jia and Percy Liang},
+    year={2018},
+    eprint={1806.03822},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+
+def _squad_metric(predictions, references):
+    squad_metric = datasets.load_metric("squad_v2")
+    return squad_metric.compute(predictions=predictions, references=references)
+
+
+def _squad_agg(key, items):
+    predictions, references = zip(*items)
+
+    return _squad_metric(predictions=predictions, references=references).get(key, 0)
+
+
+class SQuAD2(ConfigurableTask):
+    VERSION = 3
+    DATASET_PATH = "squad_v2"
+    DATASET_NAME = None
+
+    def __init__(self):
+        super().__init__(config={"metadata": {"version": self.VERSION}})
+
+    # HF changed squad on us so we have to make sure we aren't running the old one
+    assert version.parse(datasets.__version__) >= version.parse(
+        "1.11.0"
+    ), "datasets v1.11.0 or later required for SQuAD"
+
+    def has_training_docs(self):
+        return True
+
+    def has_validation_docs(self):
+        return True
+
+    def has_test_docs(self):
+        return False
+
+    def training_docs(self):
+        return self.dataset["train"]
+
+    def validation_docs(self):
+        return self.dataset["validation"]
+
+    def doc_to_text(self, doc):
+        return (
+            "Title: "
+            + doc["title"]
+            + "\n\n"
+            + "Background: "
+            + doc["context"]
+            + "\n\n"
+            + "Question: "
+            + doc["question"]
+            + "\n\n"
+            + "Answer:"
+        )
+
+    def should_decontaminate(self):
+        return True
+
+    def doc_to_decontamination_query(self, doc):
+        return doc["context"]
+
+    def doc_to_target(self, doc):
+        answer_list = doc["answers"]["text"]
+        if len(answer_list) > 0:
+            answer = answer_list[0]
+        else:
+            answer = "unanswerable"
+        return " " + answer
+
+    def construct_requests(self, doc, ctx, **kwargs):
+        """Uses RequestFactory to construct Requests and returns an iterable of
+        Requests which will be sent to the LM.
+
+        :param doc:
+            The document as returned from training_docs, validation_docs, or test_docs.
+        :param ctx: str
+            The context string, generated by fewshot_context. This includes the natural
+            language description, as well as the few shot examples, and the question
+            part of the document for `doc`.
+        """
+
+        return [
+            Instance(
+                request_type="generate_until",
+                doc=doc,
+                arguments=(ctx, {"until": ["\n"]}),
+                idx=0,
+                **kwargs,
+            ),
+            Instance(
+                request_type="loglikelihood",
+                doc=doc,
+                arguments=(ctx, " " + "unanswerable"),
+                idx=0,
+                **kwargs,
+            ),
+        ]
+
+    def process_results(self, doc, results):
+        """Take a single document and the LM results and evaluates, returning a
+        dict where keys are the names of submetrics and values are the values of
+        the metric for that one document
+
+        :param doc:
+            The document as returned from training_docs, validation_docs, or test_docs.
+        :param results:
+            The results of the requests created in construct_requests.
+        """
+
+        continuation, (logprob_unanswerable, _) = results
+
+        no_answer_probability = exp(logprob_unanswerable)
+
+        predictions = {
+            "id": doc["id"],
+            "prediction_text": continuation,
+            "no_answer_probability": no_answer_probability,
+        }
+
+        references = {
+            "id": doc["id"],
+            "answers": doc["answers"],
+        }
+
+        return {
+            "exact": (
+                predictions,
+                references,
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "f1": (
+                predictions,
+                references,
+            ),  # The F-score of predicted tokens versus the gold answer
+            "HasAns_exact": (
+                predictions,
+                references,
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "HasAns_f1": (
+                predictions,
+                references,
+            ),  # The F-score of predicted tokens versus the gold answer
+            "NoAns_exact": (
+                predictions,
+                references,
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "NoAns_f1": (
+                predictions,
+                references,
+            ),  # The F-score of predicted tokens versus the gold answer
+            "best_exact": (
+                predictions,
+                references,
+            ),  # Best exact match (with varying threshold)
+            "best_f1": (predictions, references),  # Best F1 (with varying threshold)
+        }
+
+    def aggregation(self):
+        """
+        :returns: {str: [float] -> float}
+            A dictionary where keys are the names of submetrics and values are
+            functions that aggregate a list of metrics
+        """
+        return {
+            "exact": partial(
+                _squad_agg, "exact"
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "f1": partial(
+                _squad_agg, "f1"
+            ),  # The F-score of predicted tokens versus the gold answer
+            "HasAns_exact": partial(
+                _squad_agg, "HasAns_exact"
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "HasAns_f1": partial(
+                _squad_agg, "HasAns_f1"
+            ),  # The F-score of predicted tokens versus the gold answer
+            "NoAns_exact": partial(
+                _squad_agg, "NoAns_exact"
+            ),  # Exact match (the normalized answer exactly match the gold answer)
+            "NoAns_f1": partial(
+                _squad_agg, "NoAns_f1"
+            ),  # The F-score of predicted tokens versus the gold answer
+            "best_exact": partial(
+                _squad_agg, "best_exact"
+            ),  # Best exact match (with varying threshold)
+            "best_f1": partial(
+                _squad_agg, "best_f1"
+            ),  # Best F1 (with varying threshold)
+        }
+
+    def higher_is_better(self):
+        """
+        :returns: {str: bool}
+            A dictionary where keys are the names of submetrics and values are
+            whether a higher value of the submetric is better
+        """
+        return {
+            "exact": True,  # Exact match (the normalized answer exactly match the gold answer)
+            "f1": True,  # The F-score of predicted tokens versus the gold answer
+            "HasAns_exact": True,  # Exact match (the normalized answer exactly match the gold answer)
+            "HasAns_f1": True,  # The F-score of predicted tokens versus the gold answer
+            "NoAns_exact": True,  # Exact match (the normalized answer exactly match the gold answer)
+            "NoAns_f1": True,  # The F-score of predicted tokens versus the gold answer
+            "best_exact": True,  # Best exact match (with varying threshold)
+            "best_f1": True,  # Best F1 (with varying threshold)
+        }