Instructions to use nvidia/E-RADIO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/E-RADIO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/E-RADIO", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/E-RADIO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f42c0cf1419c3b923908ad27f429407e9726e1c1b9f925e89906e26bce3465b
- Size of remote file:
- 1.11 GB
- SHA256:
- fc6244a274d1479e33f4779949f98cefeb3108b77fdc9b79c33b92295c5141d4
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