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
File size: 565 Bytes
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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 |