| --- |
| library_name: mlx |
| license: apache-2.0 |
| base_model: netflix/void-model |
| tags: |
| - mlx |
| - mlx-forge |
| - apple-silicon |
| - safetensors |
| - quantized |
| - int8 |
| --- |
| |
| # dgrauet/void-model-mlx-q8 |
|
|
| Int8 quantization (group_size 64, transformer Linear weights only) of |
| [dgrauet/void-model-mlx](https://huggingface.co/dgrauet/void-model-mlx), the MLX |
| conversion of [netflix/void-model](https://huggingface.co/netflix/void-model). |
| |
| Quantized with [mlx-forge](https://github.com/dgrauet/mlx-forge) |
| (`mlx-forge convert void-model --quantize --bits 8`). |
| |
| Good quality/memory balance (~48 GB RAM recommended for the full two-pass |
| pipeline). On 32 GB Macs use the q4 variant instead. |
| |
| ## Usage |
| |
| These weights can be used with [void-model-mlx](https://github.com/dgrauet/void-model-mlx): |
| |
| ```bash |
| python -m void_mlx.infer \ |
| --sample sample/BigBen \ |
| --pass1 weights/q8/void_pass1.safetensors \ |
| --pass2 weights/q8/void_pass2.safetensors \ |
| --base-model /path/to/CogVideoX-Fun-V1.5-5b-InP-mlx-q8 \ |
| --steps 30 --max-frames 13 --height 352 --width 624 \ |
| --output result.gif |
| ``` |
| |
| Keep `quantize_config.json` next to the weights (the loader also infers |
| bits/group_size from the weight shapes if it is missing). |
| |
| ## 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 (q8):** https://huggingface.co/dgrauet/CogVideoX-Fun-V1.5-5b-InP-mlx-q8 |
| - **bf16 variant:** https://huggingface.co/dgrauet/void-model-mlx |
| - **q4 variant:** https://huggingface.co/dgrauet/void-model-mlx-q4 |
| |
| ## Files |
| |
| - `config.json` (365.00 B) |
| - `quantize_config.json` (63.00 B) |
| - `split_model.json` (1.23 KB) |
| - `void_pass1.safetensors` (6.22 GB) |
| - `void_pass2.safetensors` (6.22 GB) |
|
|
