Instructions to use cheesebird/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cheesebird/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="cheesebird/detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("cheesebird/detr") model = AutoModelForObjectDetection.from_pretrained("cheesebird/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cheesebird/detr: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/cheesebird/detr/resolve/main/training_args.bin
- Command line
-
hf download hf://cheesebird/detr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cheesebird/detr/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 680bb7d43e730dcc0fd3c2b0c5b5b1a593de37a7bf5bb1d2cdd7c34399206b1b
- Size of remote file:
- 4.86 kB
- SHA256:
- cfc77b6031ed481d8a0e8740f915cd0fc6f064c23def154ff8a6f80013d68917
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