Instructions to use facebook/mms-tts-swh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-swh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-swh")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-swh") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-swh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 477b2f3fe209235fa61ebdd051d7f9e969ced8c0d068d2773342b0fb81b9c458
- Size of remote file:
- 145 MB
- SHA256:
- 1cbdf4e40ad12e6801391272b043f30907026891302e5dca4638da1edd14b36e
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