File size: 1,789 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
- 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)
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