How to use from the
Use from the
MLX library
# Download the model from the Hub
pip install huggingface_hub[hf_xet]

huggingface-cli download --local-dir void-model-mlx dgrauet/void-model-mlx

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

Files

  • config.json (376.00 B)
  • split_model.json (1.18 KB)
  • void_pass1.safetensors (10.38 GB)
  • void_pass2.safetensors (10.38 GB)
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