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:
- a9f85a36bb10bbdf214893dbf6bab8269ccc9e8e7786230e341e70a371dc78c4
- Size of remote file:
- 8.29 GB
- SHA256:
- d0b3dcefa093de0fedfbeddbe71c1f04d390080ec5775269e0b286d557c5dbd7
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