Instructions to use declare-lab/tango2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/tango2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="declare-lab/tango2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("declare-lab/tango2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6715bba2591a47b263d3795d3104f3660a125d2e411b17b3dbd8baf316984d4f
- Size of remote file:
- 8.54 MB
- SHA256:
- b0a4b498f27175c4d9adc422e4069d919e6874c961c0605d542ffed30778d498
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