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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0da0f6b990e083fd474a8d4abc3e378330bda8aa99b9e4a1168460378211d32
- Size of remote file:
- 2.9 GB
- SHA256:
- f99f08703756d312208388d88a443770a929e87efe3e669c07338b41b7da5bad
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