| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| model = AutoModelForCausalLM.from_pretrained("gpt2-finetuned-qa") | |
| tokenizer = AutoTokenizer.from_pretrained("gpt2-finetuned-qa") | |
| while True: | |
| prompt = input("Q: ").strip() | |
| if prompt.lower() in ["exit", "quit"]: | |
| break | |
| full_prompt = f"Q: {prompt}\nA:" | |
| inputs = tokenizer(full_prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=32, pad_token_id=tokenizer.eos_token_id) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| print() |