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:
- 2b9060f73dd4beccf0992fb244328420beb8ac85611da4c2083ebcaada65bb3b
- Size of remote file:
- 4.83 GB
- SHA256:
- 5d7b85adf7b6141985887298d10e7cf2428b91dfdc66134c9249195916922ec9
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