Instructions to use apjanco/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apjanco/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="apjanco/detr-resnet-50_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("apjanco/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("apjanco/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from apjanco/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/apjanco/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://apjanco/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/apjanco/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 0dda5da0605478b6dfa77f286c48a2443af9dcb6bf78b3e94409e034f44a4ddc
- Size of remote file:
- 4.6 kB
- SHA256:
- d02d05f45230c7dc2de85c6d1683ad0cc0fa337e1e709ef7c4898b6918084aaf
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