Instructions to use Ldicet/detr-jan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ldicet/detr-jan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Ldicet/detr-jan")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Ldicet/detr-jan") model = AutoModelForObjectDetection.from_pretrained("Ldicet/detr-jan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 852550c522f6c2a0fd1102f17ebec0bf63f3560b4bae5130599bfaae22f7d143
- Size of remote file:
- 4.98 kB
- SHA256:
- 6c72f803fd4d8314c946715f13f07fd1c72b28728106d3d094153545d3528dd5
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