Instructions to use nvidia/C-RADIOv2-g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/C-RADIOv2-g with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="nvidia/C-RADIOv2-g", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/C-RADIOv2-g", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Model Overview
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## Description
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This model performs visual feature extraction.
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# Model Overview
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[[**Github**](https://github.com/NVlabs/RADIO)] [[**CVPR 2025**](https://arxiv.org/abs/2412.07679)] [[**CVPR 2024**](https://arxiv.org/abs/2312.06709)]
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## Description
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This model performs visual feature extraction.
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