Instructions to use dgrauet/void-model-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use dgrauet/void-model-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir void-model-mlx dgrauet/void-model-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Add split_model.json so the repo identifies its recipe
Browse files- split_model.json +16 -0
split_model.json
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{
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"format": "split",
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"components": [
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"void_pass1",
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"void_pass2"
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],
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"recipe": "void-model",
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"source": "netflix/void-model",
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"license": "apache-2.0",
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"links": [
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"void-model-mlx (inference): https://github.com/dgrauet/void-model-mlx",
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"VideoX-Fun-mlx (engine): https://github.com/dgrauet/VideoX-Fun-mlx",
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"Base model weights: https://huggingface.co/dgrauet/CogVideoX-Fun-V1.5-5b-InP-mlx"
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],
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"usage_url": "https://github.com/dgrauet/void-model-mlx"
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}
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