import gradio as gr from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline from peft import PeftModel # Load tokenizer and base model base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-rw-1b", trust_remote_code=True) tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-rw-1b") # Load adapter model = PeftModel.from_pretrained(base_model, "GiteshUjgaonkar/chatbot-v02") # Pipeline generator = pipeline( "text-generation", model=model, tokenizer=tokenizer, max_length=300, temperature=0.7, top_p=0.9, do_sample=True, ) def chat(user_input, history=[]): system_prompt = "You are a kind, helpful, and friendly AI assistant." full_input = f"<|system|>\n{system_prompt}\n<|user|>\n{user_input}\n<|assistant|>\n" output = generator(full_input)[0]["generated_text"] response = output.split("<|assistant|>\n")[-1].strip() return response gr.Interface(fn=chat, inputs="text", outputs="text", title="Gitesh's Chatbot").launch()