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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef53e0f1a2f152deee0aa48d4043d00dfdccb597bda14aac468a4a1e24be8251
- Size of remote file:
- 5.78 kB
- SHA256:
- fde9a1d4a52fbf860bf2315a036ad1b24cb9f6f77cffb03f8e619039af35efe6
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