Instructions to use dummyturtle/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dummyturtle/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dummyturtle/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dummyturtle/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("dummyturtle/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dummyturtle/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/dummyturtle/detr-resnet-50_finetuned_cppe5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dummyturtle/detr-resnet-50_finetuned_cppe5/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/dummyturtle/detr-resnet-50_finetuned_cppe5/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 97e5edab8e031a961145ef0b145275a8d6a62f54cc7b9386cefa0fe950ad21f7
- Size of remote file:
- 167 MB
- SHA256:
- 62c44168d9f2414ea475d46f2860712cfdff820c7c26d9bf833910efe401ab00
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