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:
- 9bde686f0185109d78c4c0f6e3ad70bc505d14f958ccacc8ef406f8a9653a4c6
- Size of remote file:
- 5.26 GB
- SHA256:
- 6b09e4845185b7b6b6b09638c3574825e8f6efc62f0659e9bc0d7c4a05cc4a39
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