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
| # F5TTS_v1_Base | E2TTS_Base | |
| model = "F5TTS_v1_Base" | |
| ref_audio = "infer/examples/basic/basic_ref_en.wav" | |
| # If an empty "", transcribes the reference audio automatically. | |
| ref_text = "Some call me nature, others call me mother nature." | |
| gen_text = "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring." | |
| # File with text to generate. Ignores the text above. | |
| gen_file = "" | |
| remove_silence = false | |
| output_dir = "tests" | |
| output_file = "infer_cli_basic.wav" | |