Instructions to use markytools/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markytools/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="markytools/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("markytools/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("markytools/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from markytools/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/markytools/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://markytools/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/markytools/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- d282fef9dc31721a5a09e73e79f0602c9b6d3e5288cf8c7c0b7d4dae76520a84
- Size of remote file:
- 5.24 kB
- SHA256:
- 36f580a092b361729b800c5b15354fb0c8cbaeae1416f99ca4ebda8fe5ab4904
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