Instructions to use facebook/mms-tts-trn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-trn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-trn")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-trn") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-trn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4e025785ddcd9d27321da232162e7e918146f6b4929f4b81a79df35df6ab83e
- Size of remote file:
- 145 MB
- SHA256:
- 90074ba5a21ed668ccdf69277d197ec7a41ce734d040324a1289a368e71a837b
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