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:
- b90dec2b1b22cd59b540c7dcf0eb6b99584961ddcd9baa13ee0dc464129f0dff
- Size of remote file:
- 145 MB
- SHA256:
- 234c15b309f51101b5e4265ad2703a97dbc5a38bc6cb3d6ea7b7cdecd74f60b4
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