| from transformers import GPT2LMHeadModel, GPT2TokenizerFast | |
| # Load tokenizer and model | |
| model_path = "." # Path where you saved your model | |
| tokenizer = GPT2TokenizerFast.from_pretrained(model_path) | |
| model = GPT2LMHeadModel.from_pretrained(model_path) | |
| # Move model to GPU if available | |
| import torch | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| model.to(device) | |
| # Generate text from a prompt | |
| prompt = "Once upon a time" | |
| inputs = tokenizer(prompt, return_tensors="pt").to(device) | |
| outputs = model.generate( | |
| inputs.input_ids, | |
| max_length=1024, | |
| num_return_sequences=1, | |
| do_sample=True, | |
| top_k=50, | |
| top_p=0.95, | |
| temperature=0.8, | |
| pad_token_id=tokenizer.pad_token_id | |
| ) | |
| # Decode and print | |
| generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| print(generated_text) | |