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 training_args.bin from dummyturtle/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/dummyturtle/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://dummyturtle/detr-resnet-50_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dummyturtle/detr-resnet-50_finetuned_cppe5/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 75526719f81e2e9b83e3bb2075d0c0bc7159dac66931f1032b9cfa46951809e9
- Size of remote file:
- 4.54 kB
- SHA256:
- 29c4760b0b121392cbeaf54aa7876f0fd9729dee597c0fbb4bb145d2311ed153
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