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 optimizer.pt from Batr97/DETR_coco: direct link, hf CLI and curl.
- Browser
- Download file 331 MB
-
https://huggingface.co/Batr97/DETR_coco/resolve/main/optimizer.pt
- Command line
-
hf download hf://Batr97/DETR_coco/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Batr97/DETR_coco/resolve/main/optimizer.pt
331 MB
- Xet hash:
- 31310516ebb100c9e0427a9a7df224ce0f50750e8a9723310be1667ec5a501b0
- Size of remote file:
- 331 MB
- SHA256:
- 2396545c7dc0d211f2ce71436e1e65a0af4bbc1f3ef27ab0cbb9f6c1a39849fb
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