Instructions to use nickoloss/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickoloss/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nickoloss/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("nickoloss/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("nickoloss/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nickoloss/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/nickoloss/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://nickoloss/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nickoloss/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 2dfb6584757c407013828b01843bbf9ebdbb0c559b9af37d9ef6604af43d3251
- Size of remote file:
- 5.3 kB
- SHA256:
- a358f1d70de6f312e14daa146507701a65671ff699e8cb76ef74eaf0b22bcb5a
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