Instructions to use kine1004/detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kine1004/detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="kine1004/detr_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("kine1004/detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("kine1004/detr_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kine1004/detr_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/kine1004/detr_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://kine1004/detr_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kine1004/detr_finetuned_cppe5/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- c5f981e2b85ff3945ea9467b0bf63964d466e07e6ba9fcfd1e765ca0738e8eb8
- Size of remote file:
- 5.37 kB
- SHA256:
- 2d3061a2845d90d4969e4f06d5a53bc9532172b65282fda67be9ae3283dc7b5f
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