| | --- |
| | language: |
| | - it |
| | - en |
| | license: llama3 |
| | library_name: transformers |
| | base_model: meta-llama/Meta-Llama-3-8B |
| | |
| | --- |
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | import torch |
| | device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
| | |
| | MODEL_NAME = "DeepMount00/Llama-3.1-Distilled" |
| | |
| | model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.bfloat16).eval() |
| | model.to(device) |
| | tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) |
| | |
| | def generate_answer(prompt): |
| | messages = [ |
| | {"role": "user", "content": prompt}, |
| | ] |
| | model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(device) |
| | generated_ids = model.generate(model_inputs, max_new_tokens=200, do_sample=True, |
| | temperature=0.001) |
| | decoded = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) |
| | return decoded[0] |
| | |
| | prompt = "Come si apre un file json in python?" |
| | answer = generate_answer(prompt) |
| | print(answer) |
| | ``` |
| | --- |
| | ## Developer |
| | [Michele Montebovi] |
| |
|