Instructions to use facebook/mms-tts-ded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ded with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ded")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ded") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ded", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cb5ca447437dd4b1f1eb2c76b845f512b54c4e63e0c23e237cedb43c214d2e5
- Size of remote file:
- 145 MB
- SHA256:
- dc1a7aa92b681d8c1b66a08b3de83a46b0c988afc53d250bc391e6f36185e976
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