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
Record the base-model link per build, as it differs between bf16 and quantized
Browse files- split_model.json +1 -0
split_model.json
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@@ -13,6 +13,7 @@
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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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"extra_links": [
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"q8 variant: https://huggingface.co/dgrauet/void-model-mlx-q8",
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"q4 variant: https://huggingface.co/dgrauet/void-model-mlx-q4"
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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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"quantization_scope": "transformer Linear weights only",
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"extra_links": [
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"q8 variant: https://huggingface.co/dgrauet/void-model-mlx-q8",
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"q4 variant: https://huggingface.co/dgrauet/void-model-mlx-q4"
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