| import gradio as gr | |
| from transformers import pipeline | |
| # Use a different LLM (GPT-Neo instead of GPT-2) | |
| generator = pipeline('text-generation', model='EleutherAI/gpt-neo-125M') | |
| def generate_text(prompt): | |
| generated = generator( | |
| prompt, | |
| max_length=20, # Limit response length | |
| do_sample=False, # Make output deterministic | |
| temperature=0.1, # Reduce randomness | |
| repetition_penalty=2.0 # Prevent repeating words | |
| ) | |
| return generated[0]['generated_text'] | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=generate_text, | |
| inputs="text", | |
| outputs="text", | |
| title="Ask Any Question", | |
| description="Ask a question and get an answer using GPT-Neo." | |
| ) | |
| iface.launch() | |