Instructions to use piecurus/conditional-detr-resnet-50_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use piecurus/conditional-detr-resnet-50_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="piecurus/conditional-detr-resnet-50_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("piecurus/conditional-detr-resnet-50_cppe5") model = AutoModelForObjectDetection.from_pretrained("piecurus/conditional-detr-resnet-50_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1a93e66568146977a74634a3b8565ae68f1cd0f4bce6ecbae1c8c67ce26792e
- Size of remote file:
- 4.6 kB
- SHA256:
- 90f9ed9fe1c9f73440b4acd9cd37d6e2c2490385371a98e84aa921356052f420
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