Update pages/type_text.py
Browse files- pages/type_text.py +35 -37
pages/type_text.py
CHANGED
|
@@ -78,10 +78,10 @@ model_id = "meta-llama/Llama-3.2-1B-Instruct"
|
|
| 78 |
pipe = pipeline("text-generation", model=model_id, device_map=device,) # device_map="auto", torch_dtype=torch.bfloat16
|
| 79 |
|
| 80 |
|
| 81 |
-
col1, col2, col3 = st.columns([1,1,2.5])
|
| 82 |
-
col1.subheader("Score")
|
| 83 |
-
col2.subheader("SBS code")
|
| 84 |
-
col3.subheader("SBS description V2.0")
|
| 85 |
|
| 86 |
dictA = {"Score": [], "SBS Code": [], "SBS Description V2.0": []}
|
| 87 |
dfALL = pd.DataFrame.from_dict(dictA)
|
|
@@ -89,44 +89,42 @@ dfALL = pd.DataFrame.from_dict(dictA)
|
|
| 89 |
if INTdesc_input is not None and createSBScodes_clicked == True:
|
| 90 |
#for i, result in enumerate(HF_model_results_displayed):
|
| 91 |
for result in HF_model_results_displayed:
|
| 92 |
-
|
| 93 |
-
|
| 94 |
-
|
| 95 |
-
|
| 96 |
-
|
| 97 |
-
|
| 98 |
-
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
| 99 |
|
| 100 |
-
|
| 101 |
-
|
| 102 |
-
|
| 103 |
-
|
| 104 |
-
|
| 105 |
-
|
| 106 |
|
| 107 |
-
|
| 108 |
-
|
| 109 |
-
|
| 110 |
-
|
| 111 |
-
|
| 112 |
-
|
| 113 |
|
| 114 |
-
|
| 115 |
-
|
| 116 |
-
|
| 117 |
-
|
| 118 |
-
|
| 119 |
-
|
| 120 |
|
| 121 |
-
|
| 122 |
-
|
| 123 |
-
|
| 124 |
-
|
| 125 |
-
|
| 126 |
-
|
| 127 |
|
| 128 |
-
|
| 129 |
-
#dfA = pd.DataFrame.from_dict(dictA)
|
| 130 |
|
| 131 |
display_format = "ask REASONING MODEL: Which, if any, of the above Saudi Billing System descriptions corresponds best to " + INTdesc_input +"? "
|
| 132 |
st.write(display_format)
|
|
|
|
| 78 |
pipe = pipeline("text-generation", model=model_id, device_map=device,) # device_map="auto", torch_dtype=torch.bfloat16
|
| 79 |
|
| 80 |
|
| 81 |
+
#col1, col2, col3 = st.columns([1,1,2.5])
|
| 82 |
+
#col1.subheader("Score")
|
| 83 |
+
#col2.subheader("SBS code")
|
| 84 |
+
#col3.subheader("SBS description V2.0")
|
| 85 |
|
| 86 |
dictA = {"Score": [], "SBS Code": [], "SBS Description V2.0": []}
|
| 87 |
dfALL = pd.DataFrame.from_dict(dictA)
|
|
|
|
| 89 |
if INTdesc_input is not None and createSBScodes_clicked == True:
|
| 90 |
#for i, result in enumerate(HF_model_results_displayed):
|
| 91 |
for result in HF_model_results_displayed:
|
| 92 |
+
#col1.write("%.4f" % result[0]["score"])
|
| 93 |
+
#col2.write(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[0]["corpus_id"]],"SBS_Code_Hyphenated"].values[0])
|
| 94 |
+
#col3.write(SBScorpus[result[0]["corpus_id"]])
|
| 95 |
+
#dictA["Score"].append("%.4f" % result[0]["score"]), dictA["SBS Code"].append(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[0]["corpus_id"]],"SBS_Code_Hyphenated"].values[0]), dictA["SBS Description V2.0"].append(SBScorpus[result[0]["corpus_id"]])
|
| 96 |
+
dictA.update({"Score": "%.4f" % result[0]["score"], "SBS Code": df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[0]["corpus_id"]],"SBS_Code_Hyphenated"].values[0], "SBS Description V2.0": SBScorpus[result[0]["corpus_id"]]})
|
| 97 |
+
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
|
|
|
| 98 |
|
| 99 |
+
#col1.write("%.4f" % result[1]["score"])
|
| 100 |
+
#col2.write(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[1]["corpus_id"]],"SBS_Code_Hyphenated"].values[0])
|
| 101 |
+
#col3.write(SBScorpus[result[1]["corpus_id"]])
|
| 102 |
+
#dictA["Score"].append("%.4f" % result[1]["score"]), dictA["SBS Code"].append(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[1]["corpus_id"]],"SBS_Code_Hyphenated"].values[0]), dictA["SBS Description V2.0"].append(SBScorpus[result[1]["corpus_id"]])
|
| 103 |
+
dictA.update({"Score": "%.4f" % result[1]["score"], "SBS Code": df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[1]["corpus_id"]],"SBS_Code_Hyphenated"].values[0], "SBS Description V2.0": SBScorpus[result[1]["corpus_id"]]})
|
| 104 |
+
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
| 105 |
|
| 106 |
+
#col1.write("%.4f" % result[2]["score"])
|
| 107 |
+
#col2.write(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[2]["corpus_id"]],"SBS_Code_Hyphenated"].values[0])
|
| 108 |
+
#col3.write(SBScorpus[result[2]["corpus_id"]])
|
| 109 |
+
#dictA["Score"].append("%.4f" % result[2]["score"]), dictA["SBS Code"].append(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[2]["corpus_id"]],"SBS_Code_Hyphenated"].values[0]), dictA["SBS Description V2.0"].append(SBScorpus[result[2]["corpus_id"]])
|
| 110 |
+
dictA.update({"Score": "%.4f" % result[2]["score"], "SBS Code": df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[2]["corpus_id"]],"SBS_Code_Hyphenated"].values[0], "SBS Description V2.0": SBScorpus[result[2]["corpus_id"]]})
|
| 111 |
+
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
| 112 |
|
| 113 |
+
#col1.write("%.4f" % result[3]["score"])
|
| 114 |
+
#col2.write(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[3]["corpus_id"]],"SBS_Code_Hyphenated"].values[0])
|
| 115 |
+
#col3.write(SBScorpus[result[3]["corpus_id"]])
|
| 116 |
+
#dictA["Score"].append("%.4f" % result[3]["score"]), dictA["SBS Code"].append(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[3]["corpus_id"]],"SBS_Code_Hyphenated"].values[0]), dictA["SBS Description V2.0"].append(SBScorpus[result[3]["corpus_id"]])
|
| 117 |
+
dictA.update({"Score": "%.4f" % result[3]["score"], "SBS Code": df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[3]["corpus_id"]],"SBS_Code_Hyphenated"].values[0], "SBS Description V2.0": SBScorpus[result[3]["corpus_id"]]})
|
| 118 |
+
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
| 119 |
|
| 120 |
+
#col1.write("%.4f" % result[4]["score"])
|
| 121 |
+
#col2.write(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[4]["corpus_id"]],"SBS_Code_Hyphenated"].values[0])
|
| 122 |
+
#col3.write(SBScorpus[result[4]["corpus_id"]])
|
| 123 |
+
#dictA["Score"].append("%.4f" % result[4]["score"]), dictA["SBS Code"].append(df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[4]["corpus_id"]],"SBS_Code_Hyphenated"].values[0]), dictA["SBS Description V2.0"].append(SBScorpus[result[4]["corpus_id"]])
|
| 124 |
+
dictA.update({"Score": "%.4f" % result[4]["score"], "SBS Code": df_SBS.loc[df_SBS["Long_Description"] == SBScorpus[result[4]["corpus_id"]],"SBS_Code_Hyphenated"].values[0], "SBS Description V2.0": SBScorpus[result[4]["corpus_id"]]})
|
| 125 |
+
dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
|
| 126 |
|
| 127 |
+
st.write(dfALL)
|
|
|
|
| 128 |
|
| 129 |
display_format = "ask REASONING MODEL: Which, if any, of the above Saudi Billing System descriptions corresponds best to " + INTdesc_input +"? "
|
| 130 |
st.write(display_format)
|