Instructions to use k2-fsa/TTS_eval_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k2-fsa/TTS_eval_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="k2-fsa/TTS_eval_models")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("k2-fsa/TTS_eval_models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Add library_name, paper links, and citation
Verified signatureThis PR improves the model card by: - Adding `library_name: transformers` to the metadata, as the repository hosts models compatible with the Transformers library (such as Hubert and Whisper). - Linking the research papers [ZipVoice](https://huggingface.co/papers/2506.13053) and [ZipVoice-Dialog](https://huggingface.co/papers/2507.09318). - Adding a link to the official [ZipVoice GitHub repository](https://github.com/k2-fsa/ZipVoice). - Including the BibTeX citation for the associated research.ceab244
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