Instructions to use Matthijs/mms-tts-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/mms-tts-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Matthijs/mms-tts-eng")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-eng") model = AutoModelForTextToWaveform.from_pretrained("Matthijs/mms-tts-eng") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9fda9e152ead3228ab4527b6e0940bab80bea1676870e828bc0fb0bb287f33
- Size of remote file:
- 145 MB
- SHA256:
- ebcf2ddf2dc7c9e42e7936fc96e8b845cadc77af5827c0a9f9978e9e4c9517f1
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