File size: 1,947 Bytes
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library_name: mlx
license: apache-2.0
base_model: netflix/void-model
tags:
- mlx
- mlx-forge
- apple-silicon
- safetensors
- quantized
- int4
---
# dgrauet/void-model-mlx-q4
Int4 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 4`).
**This is the 32 GB configuration**: paired with the q8 base model, a full
two-pass BigBen run (30 steps, 13 frames, 352×624) peaks at ~23.7 GB —
under the 26.8 GB recommended working set of a 32 GB Apple Silicon Mac.
Quality vs the bf16 weights: PSNR ≈ 35.5 dB on the same seed.
## 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/q4/void_pass1.safetensors \
--pass2 weights/q4/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
- **q8 variant:** https://huggingface.co/dgrauet/void-model-mlx-q8
## Files
- `config.json` (365.00 B)
- `quantize_config.json` (64.00 B)
- `split_model.json` (1.40 KB)
- `void_pass1.safetensors` (4.01 GB)
- `void_pass2.safetensors` (4.01 GB)
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