Instructions to use nvidia/C-RADIOv4-SO400M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/C-RADIOv4-SO400M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/C-RADIOv4-SO400M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/C-RADIOv4-SO400M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e632fcdf0707a29780e13a02bd2a301ac36d02479a0cc63058fba5f4aac44e2f
- Size of remote file:
- 1.21 GB
- SHA256:
- d02697ede20f2716c4db12a9d3dab1c5a9b47d15a16cdcd46a69d08062b77aaf
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