Void
Collection
3 items • Updated
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
MLX format conversion of netflix/void-model.
Converted with mlx-forge.
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
config.json (376.00 B)split_model.json (1.18 KB)void_pass1.safetensors (10.38 GB)void_pass2.safetensors (10.38 GB)Quantized
Base model
netflix/void-model
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir void-model-mlx dgrauet/void-model-mlx