Instructions to use justintime47/SeedVR2-3B-MLX-Serve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use justintime47/SeedVR2-3B-MLX-Serve with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir SeedVR2-3B-MLX-Serve justintime47/SeedVR2-3B-MLX-Serve
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
SeedVR2-3B-MLX-Serve
mlx-serve-native repack of ByteDance-Seed/SeedVR2-3B for one-step diffusion image/video restoration and upscaling.
Weights are a straight fp16 passthrough from the Comfy-Org/SeedVR2 fp16 mirror (diffusion_models/seedvr2_3b_fp16.safetensors, vae/ema_vae_fp16.safetensors) plus the original repo's pos_emb.pt text-conditioning tensor โ no requantization. Converted with mlx-serve's tests/convert_seedvr2_weights.py.
Files
config.jsonโmodel_type: seedvr2dit.safetensorsโ the 635 NaDiT tensors (~6.8 GB fp16)vae.safetensorsโ encoder + decoder (~0.5 GB fp16)pos_emb.safetensorsโ the fixed text-conditioning tensor (~1 MB)
Usage
mlx-serve --model-dir ~/.mlx-serve/models/ByteDance-Seed
Serves POST /v1/images/upscales (images) and POST /v1/video/upscales (video frames).
License
Apache-2.0, inherited from the original ByteDance-Seed/SeedVR2-3B release.
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ByteDance-Seed/SeedVR2-3B