Update app.py

app.py

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