Instructions to use TendernessChen/Fin-R1-mlx-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TendernessChen/Fin-R1-mlx-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Fin-R1-mlx-fp16 TendernessChen/Fin-R1-mlx-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- 865597e4f58b96ac3a557ee6052090d5255c8431f1ead0d9e936d2d382ee9644
- Size of remote file:
- 4.62 GB
- SHA256:
- c7f0a9a406ab2541ecb1d39cb10127cfe0f7af27b90a9d6fe00e7ed03998b0f4
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