Instructions to use PierreMaxime/detr-resnet-50_finetuned_cppe5-second with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PierreMaxime/detr-resnet-50_finetuned_cppe5-second with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PierreMaxime/detr-resnet-50_finetuned_cppe5-second")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PierreMaxime/detr-resnet-50_finetuned_cppe5-second") model = AutoModelForObjectDetection.from_pretrained("PierreMaxime/detr-resnet-50_finetuned_cppe5-second", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PierreMaxime/detr-resnet-50_finetuned_cppe5-second: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/PierreMaxime/detr-resnet-50_finetuned_cppe5-second/resolve/main/training_args.bin
- Command line
-
hf download hf://PierreMaxime/detr-resnet-50_finetuned_cppe5-second/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PierreMaxime/detr-resnet-50_finetuned_cppe5-second/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 9abc96d20897cc1e44f2c50457a66ee0593f0a73c4ced1e8e576753a4ac68f31
- Size of remote file:
- 5.11 kB
- SHA256:
- 095a2b4c3ca0cc58390a03eb40ca31a89d88bfc6a32da0d31a54799dd9379295
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