Instructions to use bpdevai/test_detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bpdevai/test_detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="bpdevai/test_detr_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("bpdevai/test_detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("bpdevai/test_detr_finetuned_cppe5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da34b9eb466eea99019f649f17805bf4af7888b8d654910d8b921dae5a648679
- Size of remote file:
- 5.18 kB
- SHA256:
- dfb5b1b016fe6c9e411ad0aa21f5650b9f5bdfae6d91c31b103f2e514cbab6ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.