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:
- 1661f1d5b66369fd1e1ce333c75b069ae99cfec43dbbb3cf55344fa3c833f3aa
- Size of remote file:
- 1.54 GB
- SHA256:
- 0e887975a6e160706fd45bf71c5abce4445363016bda7a0ed4566c782a046e98
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