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:
- 6f7e59e8a4d665a91f474e621db60c458ea1caf9d6063f74c8698bf4cd6d65cc
- Size of remote file:
- 5.34 GB
- SHA256:
- 75c9276c67384f23b53a137b0edf33161b8ef881e9d8fd1532267842e3580c73
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