Instructions to use Washere-1/speecht5_tts_kin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Washere-1/speecht5_tts_kin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Washere-1/speecht5_tts_kin")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Washere-1/speecht5_tts_kin") model = AutoModelForTextToSpectrogram.from_pretrained("Washere-1/speecht5_tts_kin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- feecaeb97375423646050f04813d3221cc54ecd342680f593d5ffb07141145a8
- Size of remote file:
- 4.92 kB
- SHA256:
- e5565ca6a553cfffc47208cd91a263fc53ba36e39ecf8d2fcf9feaa463452d83
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