Instructions to use PeppX/video-pid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PeppX/video-pid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PeppX/video-pid", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: apache-2.0
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library_name: diffusers
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tags:
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- video
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- diffusion
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- vae
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- decoder
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- wan
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- pixel-space
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- pid
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pipeline_tag: image-to-video
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---
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# Video-PiD: Pixel-Space Decoder for Wan 2.1
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A small 3D pixel-space diffusion model that runs on top of Wan 2.1's VAE-decoded video frames to fix the "plastic" / waxy look of latent diffusion decoders.
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**Status: pre-alpha. No weights yet.** This repo will hold the trained checkpoints. The source code lives at [github.com/madxmoron/video-pid](https://github.com/madxmoron/video-pid).
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```
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Wan 2.1 1.3B T2V Video-PiD
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ββββββββββββ Wan-VAE ββββββββββββ residual ββββββββββββ
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β text ββββΆ decode ββββββΆβ pixel ββββΆ denoise βββΆβ pixel ββββΆ video
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β latent β (plastic) β frames β (4 steps) β frames β (sharp)
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ββββββββββββ ββββββββββββ ββββββββββββ
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```
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## Why
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Latent diffusion decoders (Wan-VAE, SD-VAE, etc.) throw away high-frequency detail and re-introduce a "waxy" smoothness. Video-PiD is a tiny post-pass that re-denoises the decoded frames in pixel space, conditioning on the original latent, and outputs a residual that adds back the detail.
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Inspired by NVIDIA's [PiD](https://research.nvidia.com/labs/sil/projects/pid/) (image-only). We extend it to video, in 3D, as a plug-in for Wan 2.1.
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## Roadmap
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- [ ] Architecture spec pinned (in progress)
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- [ ] Training run on Panda-70M / HD-VGGT
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- [ ] First checkpoint release (v0.1.0)
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- [ ] ComfyUI node
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See [github.com/madxmoron/video-pid/blob/main/docs/ROADMAP.md](https://github.com/madxmoron/video-pid/blob/main/docs/ROADMAP.md) for the full plan.
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## License
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Apache 2.0.
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## Citation
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```bibtex
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@software{video_pid_2026,
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author = {madxmoron},
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title = {Video-PiD: Pixel-Space Decoder for Wan 2.1},
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year = {2026},
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url = {https://github.com/madxmoron/video-pid}
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}
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```
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