Instructions to use facebook/mms-tts-ctg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-ctg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-ctg")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-ctg") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-ctg") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c80f56a2e9a2365b922b5e1857b2ef1a44c1678961f7391b08c0c9dd908dd7c5
- Size of remote file:
- 145 MB
- SHA256:
- 870aa51aa312c2dac365aa425dc3dfca7e3fdb9864069130eeffcdfe09dbe03e
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