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:
- c6b8aa7cc50a2fafe8202858dcb161861ac05387953ba7d0a487827ec8885e5d
- Size of remote file:
- 1.72 GB
- SHA256:
- 23e0c117de49d4ce909150fe6658d470829e6639647c7a5b035ce82e0d5b763c
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