Instructions to use sumitD/detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumitD/detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sumitD/detr_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sumitD/detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("sumitD/detr_finetuned_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2fd50118f19318f316c074dbac550cb0d55c16739a038578d6d45809a0ee54c1
- Size of remote file:
- 115 MB
- SHA256:
- 6edfea9f3c2f72e421e9f8c70e7392edb7fc651d35170994f8b336b99a39f872
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.