Instructions to use Batr97/DETR_coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Batr97/DETR_coco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Batr97/DETR_coco")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Batr97/DETR_coco") model = AutoModelForObjectDetection.from_pretrained("Batr97/DETR_coco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Batr97/DETR_coco: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Batr97/DETR_coco/resolve/main/training_args.bin
- Command line
-
hf download hf://Batr97/DETR_coco/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Batr97/DETR_coco/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 2e9e4dea11916c2b33af2a59a53c03f8486bc3b9ccdf65ebcb7f6376fa1b6527
- Size of remote file:
- 3.96 kB
- SHA256:
- 0b59e43b85b3ad45b164090d8258020f484852b7fcb6cd0ec1b191bf7fa669f0
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