Update app.py
Browse files
app.py
CHANGED
@@ -146,13 +146,11 @@ def create_vector_db(final_items):
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documents = []
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from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
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quantization_config = BitsAndBytesConfig(load_in_8bit=True)
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checkpoint = "HuggingFaceTB/SmolLM-135M"
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = AutoModelForCausalLM.from_pretrained(checkpoint
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for item in final_items:
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prompt = f"""
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@@ -164,7 +162,7 @@ def create_vector_db(final_items):
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Here is the antimony segment to summarize: {item}
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"""
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inputs = tokenizer.encode(prompt, return_tensors="pt").to(
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response = model.generate(inputs)
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documents.append(tokenizer.decode(response[0]))
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@@ -230,7 +228,8 @@ def streamlit_app():
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model_ids = list(models.keys())
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selected_models = st.multiselect(
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"Select biomodels to analyze",
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options=model_ids
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)
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if st.button("Analyze Selected Models"):
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documents = []
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from transformers import AutoModelForCausalLM, AutoTokenizer
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checkpoint = "HuggingFaceTB/SmolLM-135M"
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device = "cpu"
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
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for item in final_items:
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prompt = f"""
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Here is the antimony segment to summarize: {item}
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"""
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inputs = tokenizer.encode(prompt, return_tensors="pt").to(device)
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response = model.generate(inputs)
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documents.append(tokenizer.decode(response[0]))
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model_ids = list(models.keys())
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selected_models = st.multiselect(
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"Select biomodels to analyze",
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options=model_ids,
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default=[model_ids[0]]
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)
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if st.button("Analyze Selected Models"):
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