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)# pip install -U transformers accelerate # 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
Download config.json from SPRINGLab/SPRING_F5: direct link, hf CLI and curl.
- Browser
- Download file 366 Bytes
-
https://huggingface.co/SPRINGLab/SPRING_F5/resolve/main/config.json
- Command line
-
hf download hf://SPRINGLab/SPRING_F5/config.json
-
curl -L -o config.json https://huggingface.co/SPRINGLab/SPRING_F5/resolve/main/config.json
366 Bytes
| { | |
| "architectures": [ | |
| "SPRING_F5" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "model.SPRING_F5Config", | |
| "AutoModel": "model.SPRING_F5Model" | |
| }, | |
| "ckpt_path": "checkpoints/model_170000.pt", | |
| "model_type": "SPRING_F5", | |
| "remove_sil": true, | |
| "speed": 1.0, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.46.3", | |
| "vocab_path": "checkpoints/vocab.txt" | |
| } |