Instructions to use theroadnotbacon/BLS-Mini-Code-1.0-Q4-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use theroadnotbacon/BLS-Mini-Code-1.0-Q4-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir BLS-Mini-Code-1.0-Q4-MLX theroadnotbacon/BLS-Mini-Code-1.0-Q4-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| base_model: | |
| - CohereLabs/BLS-Mini-Code-1.0 | |
| base_model_relation: quantized | |
| library_name: mlx | |
| Generated via: | |
| ``` | |
| git clone https://github.com/eauchs/mlx-lm --single-branch --depth=1 --branch add-cohere2-moe | |
| uv venv venv | |
| source venv/bin/activate.fish | |
| uv pip install mlx[cpu] ./mlx-lm | |
| python -m mlx_lm.convert \ | |
| --hf-path "./BLS-Mini-Code-1.0" \ | |
| -q \ | |
| --q-bits 4 --q-group-size 64 \ | |
| --mlx-path ./cohere-mlx-q4 | |
| ``` | |
| Requires this fork of mlx_lm to run (main doesn't include support for cohere2_moe yet): https://github.com/eauchs/mlx-lm/tree/add-cohere2-moe |