dgrauet/void-model-mlx
MLX format conversion of netflix/void-model.
Converted with mlx-forge.
Usage
These weights can be used with void-model-mlx:
git clone https://github.com/dgrauet/VideoX-Fun-mlx.git
export VIDEOX_FUN_MLX_PATH=/path/to/VideoX-Fun-mlx
pip install mlx opencv-python-headless pillow numpy sentencepiece
python -m void_mlx.infer \
--sample sample/BigBen \
--pass1 weights/void_pass1.safetensors \
--pass2 weights/void_pass2.safetensors \
--base-model /path/to/CogVideoX-Fun-V1.5-5b-InP-mlx-q8 \
--steps 30 --max-frames 13 --height 352 --width 624 \
--low-ram --output result.gif
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)split_model.json(1.18 KB)void_pass1.safetensors(10.38 GB)void_pass2.safetensors(10.38 GB)