Update app.py

app.py

@@ -3,16 +3,26 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 from peft import PeftModel
 import torch
 
-base_model_name = "unsloth/mistral-7b-instruct-v0.3-bnb-4bit"  
-adapter_model = "jimy26/Chatbot"
+# Base model and adapter paths
+base_model_name = "unsloth/mistral-7b-instruct-v0.3-bnb-4bit"
+adapter_model_name = "jimy26/Chatbot"
 
+# Load tokenizer and base model
 tokenizer = AutoTokenizer.from_pretrained(base_model_name)
-base_model = AutoModelForCausalLM.from_pretrained(base_model_name, device_map="auto", torch_dtype=torch.float16)
-model = PeftModel.from_pretrained(base_model, adapter_model)
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_name,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
 
+# Load LoRA adapter on top
+model = PeftModel.from_pretrained(base_model, adapter_model_name)
+
+# Chat function
 def chat(prompt):
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
     outputs = model.generate(**inputs, max_new_tokens=100)
     return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
+# Gradio interface
 gr.Interface(fn=chat, inputs="text", outputs="text").launch()