Instructions to use nvidia/RADIO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/RADIO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="nvidia/RADIO", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/RADIO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05e0b4732cc8149178094ca792c53026a49b9782d8c6fc1de4c3fcc760dc4aad
- Size of remote file:
- 1.78 GB
- SHA256:
- 7a18534048fcfb79d7d0b3e654ae97ab4cbf17a734090f232ffa8cb9cb3db40b
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