Instructions to use ryfkn/DETR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryfkn/DETR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ryfkn/DETR")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ryfkn/DETR") model = AutoModelForObjectDetection.from_pretrained("ryfkn/DETR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77af77713d84773f3e73f9f207b0b882b22d359845c64739c68ab3404a2b0d86
- Size of remote file:
- 5.3 kB
- SHA256:
- 1b87b0201f21f4c12782278162f30a44f0b28f5012bc23570dd1189669d0f27e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.