Instructions to use brainworkup/Laguna-XS-2.1-oQ4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use brainworkup/Laguna-XS-2.1-oQ4e with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Laguna-XS-2.1-oQ4e brainworkup/Laguna-XS-2.1-oQ4e
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| library_name: mlx | |
| tags: | |
| - mlx | |
| - oq | |
| - quantized | |
| - omlx | |
| - oQ4e | |
| base_model: | |
| - poolside/Laguna-XS-2.1 | |
| > [!IMPORTANT] | |
| > This quantization was uploaded on **2026-08-01** and replaces a previous version. | |
| > If you downloaded this model before this date, please re-download for the updated weights. | |
| # Laguna-XS-2.1-oQ4e | |
| This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.5.4rc2) mixed-precision quantization. | |
| ## Quantization details | |
| - **Model type**: laguna | |
| - **Bits**: 4 | |
| - **Group size**: 64 | |
| - **Format**: MLX safetensors | |
| ## Quantization methods... | |
| I quantized via oMLX on my macbook pro M3 Max 48 GB machine from the base Laguna-XS-2.1 data and it worked somehow ... |