Instructions to use facebook/mms-tts-cwe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-cwe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-cwe")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-cwe") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-cwe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 953e1857c0019fb8520ca2105042efdf3b9c2ae9d888aef42a3108f91cf206e0
- Size of remote file:
- 145 MB
- SHA256:
- 0ec5028b11f83e5c9e1fb6f24ac6c7010e96d286e5a03f8ee7a66e81a22a8783
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