Instructions to use FluidInference/d3-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FluidInference/d3-coreml with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download FluidInference/d3-coreml --local-dir d3-coreml
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download nano/pos_embed.f32 from FluidInference/d3-coreml: direct link, hf CLI and curl.
- Browser
- Download file 9.44 MB
-
https://huggingface.co/FluidInference/d3-coreml/resolve/main/nano/pos_embed.f32
- Command line
-
hf download hf://FluidInference/d3-coreml/nano/pos_embed.f32
-
curl -L -o pos_embed.f32 https://huggingface.co/FluidInference/d3-coreml/resolve/main/nano/pos_embed.f32
9.44 MB
- Xet hash:
- b431d5b4165d267ed4d782f69ed3661d076241efdcd4989c19d960d412949d6d
- Size of remote file:
- 9.44 MB
- SHA256:
- 7dfb2506f3eb27d3c899d8c087bab761aaac73b74a2859d3a9cbf74e37d1953c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.