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/d3_E1536.mlpackage/Data/com.apple.CoreML/model.mlmodel from FluidInference/d3-coreml: direct link, hf CLI and curl.
- Browser
- Download file 1.61 MB
-
https://huggingface.co/FluidInference/d3-coreml/resolve/main/edge/d3_E1536.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://FluidInference/d3-coreml/edge/d3_E1536.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/FluidInference/d3-coreml/resolve/main/edge/d3_E1536.mlpackage/Data/com.apple.CoreML/model.mlmodel
1.61 MB
- Xet hash:
- c2c9a306c64932f7f5afb822d4de9965cbf028539a728229d79d2dc4f55c7d5f
- Size of remote file:
- 1.61 MB
- SHA256:
- 49b9e83c3e363c9b3f21c4d70e127e27c6ae3e7b558e64667d363d309af6f2de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.