Instructions to use jmgrodriguez/detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmgrodriguez/detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="jmgrodriguez/detr_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("jmgrodriguez/detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("jmgrodriguez/detr_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jmgrodriguez/detr_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/jmgrodriguez/detr_finetuned_cppe5/resolve/main/training_args.bin
- Command line
-
hf download hf://jmgrodriguez/detr_finetuned_cppe5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jmgrodriguez/detr_finetuned_cppe5/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 232b9f11f76af2e0d4ce99d25356d60d4e8dbfee016e52d81cc1a9874e1628a1
- Size of remote file:
- 5.11 kB
- SHA256:
- a8619ddacd8c97e254094ccb56200f72f6a48ccaf34b8567f359fcbd59461686
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