Instructions to use Jesse020202/cppe5_setup_on_roadsign_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jesse020202/cppe5_setup_on_roadsign_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Jesse020202/cppe5_setup_on_roadsign_test")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Jesse020202/cppe5_setup_on_roadsign_test") model = AutoModelForObjectDetection.from_pretrained("Jesse020202/cppe5_setup_on_roadsign_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afc3839e4b8892053ef598a1f3a5a0269a10dbae285dd5870ff771cf79c1d465
- Size of remote file:
- 174 MB
- SHA256:
- 7a740e807971c66029bd7d53693e1713062ce129058df78519f2c4afe4fb873e
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