Instructions to use declare-lab/tango2-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/tango2-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="declare-lab/tango2-full")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("declare-lab/tango2-full", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de5b84ad3027141689371b30aadb22c989f9fb0daf8161fc67b3ce03abf7cc52
- Size of remote file:
- 443 MB
- SHA256:
- 7d49e1881f38bd4f4fcaaf1c56686c02fb15f75e80dec5f773ae235b2cf1b61b
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