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| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline | |
| model_id = "TinyLlama/TinyLlama-1.1B-Chat-v1.0" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained(model_id) | |
| generator = pipeline( | |
| "text-generation", | |
| model=model, | |
| tokenizer=tokenizer, | |
| max_new_tokens=200, | |
| temperature=0.7, | |
| top_p=0.9 | |
| ) | |
| def chat(user_input): | |
| prompt = f"You are a helpful assistant.\nUser: {user_input}\nAssistant:" | |
| response = generator(prompt, return_full_text=False) | |
| return response[0]['generated_text'].strip() | |
| iface = gr.Interface( | |
| fn=chat, | |
| inputs=gr.Textbox(lines=2, placeholder="Ask a full question, like 'Where is Delhi?'"), | |
| outputs="text", | |
| title="TinyLlama Chatbot 🤖", | |
| description="Lightweight chatbot powered by TinyLlama. Works better with complete questions!" | |
| ) | |
| iface.launch() | |