Instructions to use declare-lab/tango with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/tango with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="declare-lab/tango")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("declare-lab/tango", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7605c438c7ae143d0a16d6a2ddf9c783c45468593bf2f1b6bfd7faf261e619a
- Size of remote file:
- 4.83 GB
- SHA256:
- a79eba873b614adf5a25daa9a958e254bc520100f4ccd44babda5fbb4cc565db
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