⚠️ Important: This model was automatically converted for experimentation. The following guide was not designed for this model and may not work as expected. Do not expect to function out of the box. Use at your own experimentation.

Use with mlx

pip install mlx-lm

python

from mlx_lm import load, generate

model, tokenizer = load("nhe-ai/Llasa-3B-mlx-8Bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)