Instructions to use Bytecube/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bytecube/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Bytecube/detr-resnet-50_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Bytecube/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("Bytecube/detr-resnet-50_finetuned_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e20ee1f7c07f8b07af954e017cb239d09122d7c2fd322806a3b6c598386bb1ae
- Size of remote file:
- 167 MB
- SHA256:
- a41c1417f5acd0289a8df1d91f94cb67dc403502f76f8f96a729d1e654c2c60b
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