Instructions to use facebook/mms-tts-ind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ind with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ind")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ind") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ind") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4bdfb3636b288138e46f0c57fcce883e4a89a4b7d5fa06c3c2bfa878a8e0821
- Size of remote file:
- 145 MB
- SHA256:
- 4acde8e5b3a99aa58302932d165b3eb38b405001d7004a600e6a2223e9d1c776
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