| from transformers import AutoTokenizer | |
| import transformers | |
| import torch | |
| model = "mlabonne/NeuralBeagle14-7B" | |
| messages = [{"role": "user", "content": "What is a large language model?"}] | |
| tokenizer = AutoTokenizer.from_pretrained(model) | |
| prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
| pipeline = transformers.pipeline( | |
| "text-generation", | |
| model=model, | |
| torch_dtype=torch.float16, | |
| device_map="auto", | |
| ) | |
| outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) | |
| print(outputs[0]["generated_text"]) | |