Instructions to use nvidia/RADIO-L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/RADIO-L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="nvidia/RADIO-L", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/RADIO-L", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signaturee337932
-
Update vit_patch_generator.py
Verified signaturec3cd55f
-
Update README.md
Verified signatured0099e6
-
Update README.md
Verified signaturecd613e1 -
Update README.md
Verified signaturedd96ca9
-
Update README.md
Verified signature093d083
-
Upload model (#1)
Verified signature- Upload model (e048792e24082576a734b07c13ca038577dd62f6)c5e873a -
Create preprocessor_config.json
Verified signature9f4af33 -
Create LICENSE
Verified signaturea2fe530 -
initial commit
Verified signature4d9646e