huggingface / huggingface/diffusers
F5-TTS Integration
- Lingua principale
- Python
- Stelle
- 34.5k
- Fork
- 7.3k
- Merge medio
- 3g 3h
- PR unite (30g)
- 91
Descrizione
### Model/Pipeline/Scheduler description
F5-TTS is a fully non-autoregressive text-to-speech system based on flow matching with Diffusion Transformer (DiT).
It has excellent voice cloning capabilities, and audio generation is of quite high quality.
### 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
Paper - https://arxiv.org/abs/2410.06885
Code - https://github.com/SWivid/F5-TTS?tab=readme-ov-file
Weights - https://huggingface.co/SWivid/F5-TTS
Author - @SWivid
Guida per i contributori
Apri la guida per i contributori
Direzione di ricerca
Start by reading the F5-TTS paper and the linked SWivid/F5-TTS implementation, then inspect the model weights on Hugging Face. Compare the existing diffusers architecture for audio generation with F5-TTS to determine the integration points. Done means F5-TTS is supported in diffusers, but the issue does not define specific files, tests, or acceptance criteria.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
- Stack tecnologico
- huggingface, python, pytorch
- Ambito
- audio-video-rtc, machine-learning
- Tipo di issue
- Funzionalità
- Difficoltà
- 5/5
- Tempo stimato
- Più di una settimana
- Stato di attività
- Attiva
- Chiarezza
- Da chiarire
- Idoneità per principianti
- 35/100