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:
- 25df2c3ea860b4979e477c99e1d00b36a98e634f4c1ee9d9a3584c823429d432
- Size of remote file:
- 4.83 GB
- SHA256:
- 857eb30b2752a6c08f42b490ba98367edd87d9b09e0363e2047a95b424ae60fe
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