Instructions to use Bolishetti/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bolishetti/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Bolishetti/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Bolishetti/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("Bolishetti/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Bolishetti/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Bolishetti/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://Bolishetti/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Bolishetti/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- ebf40caf1ea6212dac05b9c486e1bcb6cf440be9d76016d643f46b4c329af593
- Size of remote file:
- 3.52 kB
- SHA256:
- bcff735954ca68454e647e9183ca3425de05bf25b86e1583166416c5e38d2904
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