| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| checkpoint = 'alexghergh/gpt1' | |
| model = AutoModelForCausalLM.from_pretrained(checkpoint, trust_remote_code=True) | |
| tokenizer = AutoTokenizer.from_pretrained(checkpoint, trust_remote_code=True) | |
| prompt = 'The mastermind behind the plan was, all along, ' | |
| inputs = tokenizer(prompt, return_tensors='pt', add_special_tokens=True) | |
| generate_ids = model.generate(inputs.input_ids, | |
| max_new_tokens=40, | |
| num_beams=1, | |
| do_sample=True, | |
| top_p=0.9, | |
| temperature=0.8) | |
| print(tokenizer.batch_decode(generate_ids, | |
| skip_special_tokens=True, | |
| clean_up_tokenization_spaces=False)[0]) | |