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: 366 Bytes
8f40dc9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"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"
} |