Update pages/type_text.py
Browse files- pages/type_text.py +6 -6
pages/type_text.py
CHANGED
@@ -99,7 +99,7 @@ numMAPPINGS_input = 5
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## Define the Sentence Transformer models
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st_models = {
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'(
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'(high performance) original model for general domain: all-mpnet-base-v2': 'all-mpnet-base-v2',
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'(expected in future) fine-tuned model for medical domain: all-MiniLM-L6-v2': 'all-MiniLM-L6-v2',
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'(expected in future) fine-tuned model for medical domain: all-mpnet-base-v2': 'all-mpnet-base-v2',
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@@ -112,8 +112,8 @@ st_models = {
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#model = SentenceTransformer('clips/mfaq')
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## Create the select Sentence Transformer box
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selected_st_model = st.selectbox('
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st.write("Current selection:", selected_st_model)
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## Get the selected SentTrans model
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SentTrans_model = st_models[selected_st_model]
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@@ -121,14 +121,14 @@ SentTrans_model = st_models[selected_st_model]
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## Define the Reasoning models
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rs_models = {
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'(
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'(slower
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'(expected in future) fine-tuned model for medical domain: meta-llama/Llama-3.2-1B-Instruct': 'meta-llama/Llama-3.2-1B-Instruct',
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'(expected in future) fine-tuned model for medical domain: Qwen/Qwen2-1.5B-Instruct': 'Qwen/Qwen2-1.5B-Instruct',
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}
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## Create the select Reasoning box
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selected_rs_model = st.selectbox('Current selected Reasoning model:', list(rs_models.keys()))
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#st.write("Current selection:", selected_rs_model)
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## Get the selected Reasoning model
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## Define the Sentence Transformer models
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st_models = {
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'(higher speed) original model for general domain: all-MiniLM-L6-v2': 'all-MiniLM-L6-v2',
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'(high performance) original model for general domain: all-mpnet-base-v2': 'all-mpnet-base-v2',
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'(expected in future) fine-tuned model for medical domain: all-MiniLM-L6-v2': 'all-MiniLM-L6-v2',
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'(expected in future) fine-tuned model for medical domain: all-mpnet-base-v2': 'all-mpnet-base-v2',
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#model = SentenceTransformer('clips/mfaq')
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## Create the select Sentence Transformer box
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selected_st_model = st.selectbox('Current selected Sentence Transformer model:', list(st_models.keys())) # or 'Choose a Sentence Transformer Model'
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#st.write("Current selection:", selected_st_model)
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## Get the selected SentTrans model
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SentTrans_model = st_models[selected_st_model]
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## Define the Reasoning models
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rs_models = {
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'(medium speed) original model for general domain: meta-llama/Llama-3.2-1B-Instruct': 'meta-llama/Llama-3.2-1B-Instruct',
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'(slower speed) original model for general domain: Qwen/Qwen2-1.5B-Instruct': 'Qwen/Qwen2-1.5B-Instruct',
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'(expected in future) fine-tuned model for medical domain: meta-llama/Llama-3.2-1B-Instruct': 'meta-llama/Llama-3.2-1B-Instruct',
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'(expected in future) fine-tuned model for medical domain: Qwen/Qwen2-1.5B-Instruct': 'Qwen/Qwen2-1.5B-Instruct',
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}
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## Create the select Reasoning box
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selected_rs_model = st.selectbox('Current selected Reasoning model:', list(rs_models.keys())) # or 'Choose a Reasoning Model'
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#st.write("Current selection:", selected_rs_model)
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## Get the selected Reasoning model
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