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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/RADIO", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -7,7 +7,7 @@ Mike Ranzinger, Greg Heinrich, Jan Kautz, Pavlo Molchanov
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[NVIDIA Research](https://www.nvidia.com/en-us/research/)
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\[[Paper](https://arxiv.org/abs/2312.06709)\]\[[BibTex](#citing-radio)\]
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## Pretrained Models
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[NVIDIA Research](https://www.nvidia.com/en-us/research/)
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\[[Paper](https://arxiv.org/abs/2312.06709)\]\[[BibTex](#citing-radio)\]\[[GitHub examples](https://github.com/NVlabs/RADIO)\]
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## Pretrained Models
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