Instructions to use facebook/mms-tts-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-eng")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-eng") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-eng") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b5bdf903b3347a6f4b7511c16dd6baa8e2e5feafc8d6710bd9a2a1a9bb383dd
- Size of remote file:
- 145 MB
- SHA256:
- f184227f5c3298e02714322ab0b35932c534d1c36095198b69c6b34033f1a39d
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