Instructions to use tevino/Hy-MT2-7B-oQ6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use tevino/Hy-MT2-7B-oQ6 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Hy-MT2-7B-oQ6 tevino/Hy-MT2-7B-oQ6
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Create README.md
Browse files
README.md
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---
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library_name: mlx
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tags:
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- mlx
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- oq
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- quantized
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- mtp
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base_model:
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- tencent/Hy-MT2-7B
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---
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# Hy-MT2-7B-oQ6
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This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.3.9) mixed-precision quantization.
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## Quantization details
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- **Model type**: hunyuan_v1_dense
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- **Bits**: 6
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- **Group size**: 64
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- **Format**: MLX safetensors
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