Instructions to use mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir SFR-Iterative-DPO-LLaMA-3-8B-R-4bit mlx-community/SFR-Iterative-DPO-LLaMA-3-8B-R-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- a1266b0aba3890b3a2c6daae51af2051335b112c3b9c79419ba200551880a810
- Size of remote file:
- 4.52 GB
- SHA256:
- e645db2b42925c308ca0f887dbde5f0e4448ef1184ea212959765b548f99c6ad
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