Instructions to use memogamd/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use memogamd/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="memogamd/detr-resnet-50_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("memogamd/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("memogamd/detr-resnet-50_finetuned_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edc3d7d756b4ee7706854ed1e13e271b3897070ec26c7c60559a33ab60dd1a13
- Size of remote file:
- 167 MB
- SHA256:
- 07807f80de8226305f276976891ea0aa393acb4f5163ffa49059b45fa036c6a3
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