Instructions to use fav-kky/SpeechT5-base-cs-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/SpeechT5-base-cs-tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="fav-kky/SpeechT5-base-cs-tts")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("fav-kky/SpeechT5-base-cs-tts") model = AutoModelForTextToSpectrogram.from_pretrained("fav-kky/SpeechT5-base-cs-tts") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29a74972125431cee219ab1f4ae7eb05034a2504059f43cf48f963fa4bf14bff
- Size of remote file:
- 238 kB
- SHA256:
- ef804c879bc2e4fd5dc5a49825a79b37dd85bd6072377480146c641ef3365eeb
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