Instructions to use TiGa-RCE/LFM2-1.2B-MLX-oQ4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TiGa-RCE/LFM2-1.2B-MLX-oQ4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir LFM2-1.2B-MLX-oQ4 TiGa-RCE/LFM2-1.2B-MLX-oQ4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 501 Bytes
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library_name: mlx
tags:
- mlx
- oq
- quantized
---
> [!IMPORTANT]
> This quantization was uploaded on **2026-06-30** and replaces a previous version.
> If you downloaded this model before this date, please re-download for the updated weights.
# LFM2-1.2B-MLX-oQ4
This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.4.5.dev1) mixed-precision quantization.
## Quantization details
- **Model type**: lfm2
- **Bits**: 4
- **Group size**: 64
- **Format**: MLX safetensors
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