Instructions to use declare-lab/tango-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/tango-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="declare-lab/tango-full")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("declare-lab/tango-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4080b3f225dc45c14af8f92dc2c3fc3daeaae8f9d7b605bc63a00f25b7bf3f11
- Size of remote file:
- 4.83 GB
- SHA256:
- a7b8dff1dac23394e412113653cac8dccba055b598c48b5605c4cf690e725c56
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