Instructions to use MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit --local-dir gemma2-9b-33dataset-finetuned-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MayankBitcot/gemma2-9b-33dataset-finetuned-mlx-4Bit/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- f27164cb42d0755a05603be16cf6c45623a00606e5394f978d4751cf7d3ddb4e
- Size of remote file:
- 34.4 MB
- SHA256:
- 460d2b08bc29bfc70fbf481b033bbc517969fcc56b374ce8f95b9b40de8969c2
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