Instructions to use nvidia/RADIO-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/RADIO-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="nvidia/RADIO-B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/RADIO-B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a0dd7804f70fe14d05bb513fa5f8d65c5af37f2e0d84c4e89ce71393925a9f2
- Size of remote file:
- 395 MB
- SHA256:
- d58db8f4ba0d3f6ea2dc8bc9bc846e6f059c656160f23e576c0b15368b8c4770
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