Instructions to use hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech") model = AutoModelForTextToSpectrogram.from_pretrained("hf-internal-testing/tiny-random-SpeechT5ForTextToSpeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 774700a8ff44d4a9d8342251e1d856a39e3b503417aa9293e1cbc05cf877b051
- Size of remote file:
- 5.34 MB
- SHA256:
- f82760a8ace28c641b2474cabf7bad1d04ecfc9c62568f1681aea1a514810098
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