Instructions to use emre/speecht5_tts_tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre/speecht5_tts_tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="emre/speecht5_tts_tr")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("emre/speecht5_tts_tr") model = AutoModelForTextToSpectrogram.from_pretrained("emre/speecht5_tts_tr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e61f5c8ecece09235fd8d57c54235345dfbcdcb2f7bfd0e9637365d71031c63
- Size of remote file:
- 585 MB
- SHA256:
- 666ba2637140798a6dc439d71776ddcd8421bc073edab652f1f458f58b5e2fe9
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