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:
- 4c339f5c7e8d5b49ea5f97920b38c06c873396d310d5d0c5bb007a913edec53a
- Size of remote file:
- 649 MB
- SHA256:
- 6bff4bd732d815136652d454598e8fe6c6f4e658716d5e6a697f0e6b60bd8a98
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