DeepMount00/Murai-350M-v0.1-beta

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Usage

from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM

model_id = "DeepMount00/Murai-350M-v0.1-beta"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True,
)

prompt = [{'role': 'user', 'content': """Scrivi una funzione python che somma due numeri"""}]

inputs = tokenizer.apply_chat_template(
    prompt,
    add_generation_prompt=True,
    return_tensors='pt'
)
tokens = model.generate(
    inputs.to(model.device),
    max_new_tokens=256,
    temperature=0.1,
    repetition_penalty=1.2,
    do_sample=True
)

print(tokenizer.decode(tokens[0], skip_special_tokens=False))

Citation

@misc{deepmount_llm_2024,
  title={Deep LLM: A 350M Parameter Language Model with 42 Layers},
  author={MicheleMontebovi},
  year={2025},
  url={https://huggingface.co/DeepMount00/Murai-350M-v0.1-beta}
}

License

Apache 2.0