Instructions to use SPRINGLab/SPRING_F5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SPRINGLab/SPRING_F5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="SPRINGLab/SPRING_F5", trust_remote_code=True)# Load model directly from transformers import SPRING_F5 model = SPRING_F5.from_pretrained("SPRINGLab/SPRING_F5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 267 Bytes
8f40dc9 | 1 2 3 4 5 6 7 8 9 | from f5_tts.model.backbones.dit import DiT
from f5_tts.model.backbones.mmdit import MMDiT
from f5_tts.model.backbones.unett import UNetT
from f5_tts.model.cfm import CFM
from f5_tts.model.trainer import Trainer
__all__ = ["CFM", "UNetT", "DiT", "MMDiT", "Trainer"]
|