huggingface / huggingface/diffusers

F5-TTS Integration

Aperta
#10,043 12 commenti 0 reazioni 0 assegnatari Vedi su GitHub
contributions-welcome help wanted
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

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.