Instructions to use nextt/detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nextt/detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nextt/detr_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("nextt/detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("nextt/detr_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nextt/detr_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/nextt/detr_finetuned_cppe5/resolve/5146dda0404b599bdf16e75ed5cc27d1b07bb98e/training_args.bin
- Command line
-
hf download hf://nextt/detr_finetuned_cppe5@5146dda0404b599bdf16e75ed5cc27d1b07bb98e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nextt/detr_finetuned_cppe5/resolve/5146dda0404b599bdf16e75ed5cc27d1b07bb98e/training_args.bin
4.98 kB
- Xet hash:
- a93865bcc02a987df5c38a9ab78868a00d889e5e92262a8a1365361d3a3a3f06
- Size of remote file:
- 4.98 kB
- SHA256:
- aeac5f11ad2a2b6f0b4e208e7b9cb1ccd48e3a8dd5624ac9d4f184d0eee3b23c
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