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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("k2-fsa/TTS_eval_models", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add library_name, paper links, and citation
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding
library_name: transformersto the metadata, as the repository hosts models compatible with the Transformers library (such as Hubert and Whisper). - Linking the research papers ZipVoice and ZipVoice-Dialog.
- Adding a link to the official ZipVoice GitHub repository.
- Including the BibTeX citation for the associated research.
Thanks!
zhu-han changed pull request status to merged