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:
- f18cce7289f6ba407cb69240915a61e86797bb6d5e8aa8ece80267bcc6e6b06f
- Size of remote file:
- 1.3 GB
- SHA256:
- 03534ca8b7a26b0cbf69073b944fdd47f41aedad1b3b01c1e387c27191abc8de
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