epfl-llm/guidelines
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How to use mlx-community/meditron-7b with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir meditron-7b mlx-community/meditron-7b
The Model mlx-community/meditron-7b was converted to MLX format from epfl-llm/meditron-7b using mlx-lm version 0.20.1.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/meditron-7b")
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)
4-bit