Instructions to use facebook/mms-tts-mai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-mai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-mai")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-mai") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-mai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ebbd7465c4c7fbce44b4e34176498ef3d57d472d9bae41043f79e65c3450e85
- Size of remote file:
- 145 MB
- SHA256:
- af00259d232e39186086b4bc8c4b61384560def7db5ba196aae7d96410d05304
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