Instructions to use facebook/mms-tts-ewe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ewe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ewe")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ewe") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ewe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2daf53b383e7dc45060abe3632110f4c91e00b92d7bc562a72c02ddcb127a92
- Size of remote file:
- 145 MB
- SHA256:
- 17d7cc3d386a6e20634812a80987b9f884058f618ff3d217fd4344f09566e5cb
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