v1

app.py

@@ -11,11 +11,36 @@ st.title("Mistral Model Integration")
 instruction = st.text_area("Enter your prompt:")
 
 # Function to interact with Mistral Model
+# def mistral_model(prompt, token_limit):
+#     # Your model loading and inference code here (from the code you provided)
+#     # ...
+
+#     return responses
+
 def mistral_model(prompt, token_limit):
-    # Your model loading and inference code here (from the code you provided)
-    # ...
+    # Initialize the model and tokenizer
+    model_name = "bn22/Mistral-7B-Instruct-v0.1-sharded"
+    adapters_name = "atharvapawar/flaskCodemistral-7b-mj-finetuned"
+    device = "cuda"  # Use "cuda" for GPU or "cpu" for CPU
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+
+    # Load the adapter
+    model = PeftModel.from_pretrained(model, adapters_name)
+
+    # Generate responses
+    text = "[INST]" + prompt + "[/INST]"
+    encoded = tokenizer(text, return_tensors="pt", add_special_tokens=False)
+    model.to(device)
+    generated_ids = model.generate(**encoded, max_length=token_limit, do_sample=True)
+    decoded = tokenizer.batch_decode(generated_ids)
+
+    return decoded
+
+        
+
 
-    return responses
 
 # Check if the user entered a prompt
 if instruction: