Instructions to use realtime-speech/s2tmedium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use realtime-speech/s2tmedium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="realtime-speech/s2tmedium")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("realtime-speech/s2tmedium") model = AutoModel.from_pretrained("realtime-speech/s2tmedium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2433cb53aed3e7a25db8620b033561e0cf1136911be5f6dbfb5ad4fbb3a7faa
- Size of remote file:
- 4.84 GB
- SHA256:
- c4c909af3764375abe4cfc5727768e582c1735db7990bbad3129a7d4655cc7d6
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