huggingface / huggingface/diffusers

Add support for JoyAI-Video-Edit

Aperta
#14,524 1 commento 0 reazioni 0 assegnatari Vedi su GitHub
Lingua principale
Python
Stelle
34.5k
Fork
7.3k
Merge medio
3g 3h
PR unite (30g)
91

Descrizione

### Model/Pipeline/Scheduler description

[JoyAI-Video-Edit](https://github.com/jd-opensource/JoyAI-Video-Edit) is an instruction-guided video editing model based on the JoyAI streaming architecture.

It performs causal, chunk-wise video denoising with a per-layer KV cache. Each chunk attends to previously denoised chunks and may additionally attend to an optional reference image.

Prompt embeddings are produced by the external [MiMo-VL](https://huggingface.co/XiaomiMiMo/MiMo-VL-7B-RL-2508) model.

### Open source status

- [x] The model implementation is available.
- [x] The model weights are available (Only relevant if addition is not a scheduler).

### Provide useful links for the implementation

- Reference implementation: https://github.com/jd-opensource/JoyAI-Video-Edit
- Original checkpoint: https://huggingface.co/jdopensource/JoyAI-Video-Edit
- MiMo-VL: https://huggingface.co/XiaomiMiMo/MiMo-VL-7B-RL-2508

Guida per i contributori

Apri la guida per i contributori

Direzione di ricerca

No repository files, tests, or entry points are named. Start by comparing the linked reference implementation and checkpoint with existing video model integrations in diffusers, then determine how MiMo-VL prompt embeddings, causal KV caching, chunk-wise denoising, and optional reference images fit the project. Done means JoyAI-Video-Edit is supported using the linked model resources.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
python, pytorch
Ambito
computer-vision, machine-learning
Tipo di issue
Funzionalità
Difficoltà
5/5
Tempo stimato
Più di una settimana
Stato di attività
Tranquilla
Chiarezza
Da chiarire
Idoneità per principianti
35/100

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