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