Instructions to use woutervd/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use woutervd/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="woutervd/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("woutervd/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("woutervd/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from woutervd/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/woutervd/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://woutervd/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/woutervd/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 7c2f38729086ae7f7d52f8eecedaf4706ffb86c1220aa2ecb8375d1c573a8644
- Size of remote file:
- 3.96 kB
- SHA256:
- a6c7cb74db0c3232f07b022bc08fd89666868be6617f90f7b505c7368a28edf0
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