| from transformers import GPT2LMHeadModel, GPT2Tokenizer |
|
|
| # Load pre-trained model and tokenizer |
| model = GPT2LMHeadModel.from_pretrained('gpt2') |
| tokenizer = GPT2Tokenizer.from_pretrained('gpt2') |
|
|
| # Define prompt and generate text |
| prompt = "Generate a 3D model of a hugging face" |
| input_ids = tokenizer.encode(prompt, return_tensors='pt') |
| output = model.generate(input_ids, max_length=50, do_sample=True) |
| |
| # Convert output to text and print |
| output_text = tokenizer.decode(output[0], skip_special_tokens=True) |
| print(output_text) |
| |
