Update pages/type_text.py
Browse files- pages/type_text.py +2 -2
pages/type_text.py
CHANGED
@@ -9,7 +9,7 @@ from sentence_transformers import SentenceTransformer, util
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import os
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os.getenv("HF_TOKEN")
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st.header("Map internal descriptions to SBS codes using Sentence Transformer
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st.subheader("Select specific Chapter for quicker results")
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#df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows.csv")
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df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows_with_total.csv")
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@@ -171,7 +171,7 @@ dictA = {"Score": [], "SBS Code": [], "SBS Description V2.0": []}
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dfALL = pd.DataFrame.from_dict(dictA)
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if INTdesc_input is not None and if st.button(
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#my_model_results = pipeline("ner", model= "checkpoint-92")
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HF_model_results = util.semantic_search(INTdesc_embedding, SBScorpus_embeddings)
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HF_model_results_sorted = sorted(HF_model_results, key=lambda x: x[1], reverse=True)
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import os
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os.getenv("HF_TOKEN")
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st.header("Map internal descriptions to SBS codes using Sentence Transformer plus Reasoning Models")
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st.subheader("Select specific Chapter for quicker results")
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#df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows.csv")
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df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows_with_total.csv")
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dfALL = pd.DataFrame.from_dict(dictA)
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if INTdesc_input is not None and if st.button("user_clickedSBS"):
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#my_model_results = pipeline("ner", model= "checkpoint-92")
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HF_model_results = util.semantic_search(INTdesc_embedding, SBScorpus_embeddings)
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HF_model_results_sorted = sorted(HF_model_results, key=lambda x: x[1], reverse=True)
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