Instructions to use nvidia/C-RADIOv2-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/C-RADIOv2-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="nvidia/C-RADIOv2-B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/C-RADIOv2-B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add library name and pipeline tag
#2
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,4 +1,6 @@
|
|
| 1 |
---
|
|
|
|
|
|
|
| 2 |
license: other
|
| 3 |
license_name: nvidia-open-model-license
|
| 4 |
license_link: https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
|
|
|
|
| 1 |
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
pipeline_tag: image-feature-extraction
|
| 4 |
license: other
|
| 5 |
license_name: nvidia-open-model-license
|
| 6 |
license_link: https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
|