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title: README
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MLX Community
A community org for model weights compatible with mlx-examples powered by MLX.
These are pre-converted weights and ready to be used in the example scripts.
Quick start for LLMs
Install mlx-lm
:
pip install mlx-lm
You can use mlx-lm
from the command line. For example:
mlx_lm.generate --model mlx-community/Mistral-7B-Instruct-v0.3-4bit --prompt "hello"
This will download a Mistral 7B model from the Hugging Face Hub and generate text using the given prompt.
For a full list of options run:
mlx_lm.generate --help
To quantize a model from the command line run:
mlx_lm.convert --hf-path mistralai/Mistral-7B-Instruct-v0.3 -q
For more options run:
mlx_lm.convert --help
You can upload new models to Hugging Face by specifying --upload-repo
to
convert
. For example, to upload a quantized Mistral-7B model to the
MLX Hugging Face community you can do:
mlx_lm.convert \
--hf-path mistralai/Mistral-7B-Instruct-v0.3 \
-q \
--upload-repo mlx-community/my-4bit-mistral
For more details on the API checkout the full README
Other Examples:
For more examples, visit the MLX Examples repo. The repo includes examples of:
Parameter efficient fine tuning with LoRA
Speech recognition with Whisper
Image generation with Stable Diffusion
and many other examples of different machine learning applications and algorithms.