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| .. | ||
| generate.py | ||
| models.py | ||
| README.md | ||
| requirements.txt | ||
| utils.py | ||
LLMs in MLX with GGUF
An example generating text using GGUF format models in MLX.1
Note
MLX is able to read most quantization formats from GGUF directly. However, only a few quantizations are supported directly:
Q4_0,Q4_1, andQ8_0. Unsupported quantizations will be cast tofloat16.
Setup
Install the dependencies:
pip install -r requirements.txt
Run
Run with:
python generate.py \
--repo <hugging_face_repo> \
--gguf <file.gguf> \
--prompt "Write a quicksort in Python"
For example, to generate text with Mistral 7B use:
python generate.py \
--repo TheBloke/Mistral-7B-v0.1-GGUF \
--gguf mistral-7b-v0.1.Q8_0.gguf \
--prompt "Write a quicksort in Python"
Run python generate.py --help for more options.
Models that have been tested and work include:
-
TheBloke/Mistral-7B-v0.1-GGUF, for quantized models use:
mistral-7b-v0.1.Q8_0.ggufmistral-7b-v0.1.Q4_0.gguf
-
TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF, for quantized models use:
tinyllama-1.1b-chat-v1.0.Q8_0.gguftinyllama-1.1b-chat-v1.0.Q4_0.gguf
-
For more information on GGUF see the documentation. ↩︎