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| license: apache-2.0 | |
| datasets: | |
| - FastVideo/Wan2.2-Syn-121x704x1280_32k | |
| base_model: | |
| - Wan-AI/Wan2.2-TI2V-5B-Diffusers | |
| library_name: fastvideo | |
| tags: | |
| - video-generation | |
| - text-to-video | |
| - wan | |
| - int8 | |
| - quantization | |
| - apple-silicon | |
| pipeline_tag: text-to-video | |
| # FastMetal-5B-QAD | |
| **3-step text-to-video, INT8 pre-quantized for Apple Silicon.** | |
| The mid-tier FastMetal model — a DMD2-distilled Wan2.2 TI2V 5B with a | |
| quantization-aware-trained INT8 DiT. 720p-native, pre-quantized: no | |
| startup quantization. | |
| ## What's inside | |
| | Path | Contents | | |
| |---|---| | |
| | `mlx_dit.safetensors` / `mlx_dit.json` | INT8 (affine, group-64) DiT | | |
| | `text_encoder/`, `vae/`, `tokenizer/`, `scheduler/` | everything needed to run standalone | | |
| ## Quickstart | |
| Requires macOS with Apple silicon (MPS) and Python 3.11+: | |
| ```bash | |
| pip install torch transformers mlx safetensors av imageio imageio-ffmpeg | |
| git clone https://github.com/FastVideo/FastVideo.git | |
| cd FastVideo | |
| python examples/inference/basic/mlx_wan22_generate.py \ | |
| --text-encoder-root ./FastMetal-5B-QAD \ | |
| --mlx-checkpoint ./FastMetal-5B-QAD \ | |
| --vae-root ./FastMetal-5B-QAD/vae \ | |
| --prompt "a river winding through a fantasy valley at golden hour" \ | |
| --fast | |
| ``` | |
| ## Model details | |
| | | | | |
| |---|---| | |
| | Base model | Wan 2.2 TI2V 5B | | |
| | Distillation | DMD2, 3 denoising steps | | |
| | Quantization | affine INT8, group size 64, QAT-trained | | |
| | Resolution | 704×1280 (720p), 121 frames | | |
| | Flow shift | 5.0 | | |
| | DiT weights | ~5 GB (INT8) | | |
| ## Training | |
| DMD2 distillation of the Wan 2.2 TI2V 5B teacher onto an INT8 student on | |
| NVIDIA GB200 clusters, with quantization-aware training (affine INT8, | |
| group 64). Training corpus: `FastVideo/Wan2.2-Syn-121x704x1280_32k`. | |
| ## FastMetal family | |
| | Model | Tier | | |
| |---|---| | |
| | [FastMetal-1.3B-QAD](https://huggingface.co/FastVideo/FastMetal-1.3B-QAD) | Entry — 16 GB+ class Macs | | |
| | **FastMetal-5B-QAD** | Mid — 720p | 16 GB+ class Macs | | |
| | [FastMetal-14B-QAD](https://huggingface.co/FastVideo/FastMetal-14B-QAD) | Quality — 24 GB+/ Ideally 36 Macs | | |