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 pytorch_model.bin from Batr97/DETR_coco: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Batr97/DETR_coco/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Batr97/DETR_coco/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Batr97/DETR_coco/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- eac6af41915e0b805d2ece6a3ce0e451e48efaab962d8697cfb1d0a04ff2f882
- Size of remote file:
- 167 MB
- SHA256:
- c29308231671b6b6fe5abfb809c0d2e147ecd20665484f753a9661b4b60e5d1d
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