wlsaidhi's picture
Add INT4 MLX model card and metadata
b2e1973 verified
|
Raw
History Blame Contribute Delete
2.86 kB
---
license: other
license_name: minimax-h3-community
license_link: https://huggingface.co/FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree/blob/main/LICENSE
base_model: FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree
library_name: fastvideo
pipeline_tag: text-to-video
tags:
- mlx
- apple-silicon
- minimax-h3
- fasth3
- text-to-video
- audio
- quantized
- int4
---
# FastH3 Preview v1 Dense DataFree MLX INT4
This repository contains the ready-to-run **INT4 MLX DiT** for
[FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree](https://huggingface.co/FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree). It avoids the local
conversion step and its temporary unified-memory requirement on Apple silicon.
The checkpoint is the dense-attention, step-1000, four-forward Preview v1 model.
Quantization is affine, weight-only INT4 with group size 64. Activations
remain BF16. This export is dense-only and does not support `--vsa`.
## Files
| File | Purpose |
| --- | --- |
| `mlx_h3_dit.safetensors` | Quantized H3 DiT weights, 10.74 GiB |
| `mlx_h3_dit.json` | Architecture, quantization, and cached AdaLN schedule |
| `conversion_manifest.json` | Source revision, converter version, validation, and checksums |
Weights SHA-256: `dcee86c17197c621a0e3d3ba9541cb6ef5764cd0c258beb7b044fb12b217e948`
## Download
Download the shared H3 components once. They include the tokenizer, Qwen3-VL
text encoder, video VAE, and audio VAE:
```bash
hf download FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree \
--revision f624f08c6c279ab43534c003e556fc5b295b6558 \
--local-dir ./FastH3-Preview-v1-Dense-DataFree
```
Then download this ready-to-run MLX DiT:
```bash
hf download FastVideo/FastVideo-FastH3-4-step-Preview-v1-Dense-DataFree-MLX-INT4 \
--local-dir ./FastH3-MLX-INT4
```
## Run on Apple silicon
From a current FastVideo checkout:
```bash
uv venv --python 3.12 --seed
source .venv/bin/activate
uv pip install -e ".[mlx]"
```
```bash
python examples/inference/basic/mlx_fasth3.py \
--model-root ./FastH3-Preview-v1-Dense-DataFree \
--mlx-checkpoint ./FastH3-MLX-INT4 \
--prompt '(S1) A presenter says <d>[English] Fast H3 runs on Apple silicon.</d>' \
--height 480 --width 832 --num-frames 124 --steps 4 --seed 2026 \
--output-path ./outputs/fasth3_int4.mp4
```
The MLX runtime loads one heavyweight component at a time. The source model's
MiniMax H3 Community License applies to this converted checkpoint.
## Validation and provenance
The conversion used FastVideo commit
`cf6a00b9be4675602126d6aeab902ad9a74810ea` with MLX
`0.32.2` on an Apple M4 Max. FastVideo
verified all 13 source transformer shards, opened the safetensors header,
validated 1,464 tensors and the quantization manifest, loaded the checkpoint,
and completed a 124-frame 832x480 generation with the full H3 VAE.