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:
- 4c1aca8b26afa9302eb82c4870604ddd0abef699fcba5075f26e946f5dbbd5d8
- Size of remote file:
- 5.34 MB
- SHA256:
- 4d63bfdc9533504e0d813ddcde270c1ebc050c7ceece143d01905b38277e02c7
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