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 edge/pos_embed.f32 from FluidInference/d3-coreml: direct link, hf CLI and curl.
- Browser
- Download file 7.08 MB
-
https://huggingface.co/FluidInference/d3-coreml/resolve/main/edge/pos_embed.f32
- Command line
-
hf download hf://FluidInference/d3-coreml/edge/pos_embed.f32
-
curl -L -o pos_embed.f32 https://huggingface.co/FluidInference/d3-coreml/resolve/main/edge/pos_embed.f32
7.08 MB
- Xet hash:
- 2a0d72db1bfd62b55913358c3a3c4bb1076fd4c4dafc1b3747ed14015979ac4f
- Size of remote file:
- 7.08 MB
- SHA256:
- 9a883241c3d1f55bbb10b1aca1202f463dc0ebe0efba8d11c4d00aaf1e95a4db
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.