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
- LM Studio
File size: 932 Bytes
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library_name: mlx
license: apache-2.0
base_model: netflix/void-model
tags:
- mlx
- mlx-forge
- apple-silicon
- safetensors
---
# dgrauet/void-model-mlx
MLX format conversion of [netflix/void-model](https://huggingface.co/netflix/void-model).
Converted with [mlx-forge](https://github.com/dgrauet/mlx-forge).
## Usage
These weights can be used with [void-model-mlx](https://github.com/dgrauet/void-model-mlx).
## Related Projects
- **void-model-mlx (inference):** https://github.com/dgrauet/void-model-mlx
- **VideoX-Fun-mlx (engine):** https://github.com/dgrauet/VideoX-Fun-mlx
- **Base model weights:** https://huggingface.co/dgrauet/CogVideoX-Fun-V1.5-5b-InP-mlx
- **q8 variant:** https://huggingface.co/dgrauet/void-model-mlx-q8
- **q4 variant:** https://huggingface.co/dgrauet/void-model-mlx-q4
## Files
- `config.json` (376.00 B)
- `void_pass1.safetensors` (10.38 GB)
- `void_pass2.safetensors` (10.38 GB)
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