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
Update model.py
Browse files
model.py
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@@ -52,6 +52,7 @@ class SPRING_F5Model(PreTrainedModel):
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ckpt_file,
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mel_spec_type="vocos",
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vocab_file=vocab_path,
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device=self._device
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)
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ckpt_file,
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mel_spec_type="vocos",
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vocab_file=vocab_path,
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use_ema=False,
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device=self._device
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)
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