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:
- a293ebe7892558aa09c2314be629f4738ede71c3034d61c48797fc9502bb744a
- Size of remote file:
- 1.54 GB
- SHA256:
- 6d51dd5d8707ec04af92d054f7918d2b0c9c09eda122da668a73c32907ff7d3b
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