Instructions to use aaa950739/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaa950739/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="aaa950739/trained_model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("aaa950739/trained_model") model = AutoModelForObjectDetection.from_pretrained("aaa950739/trained_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 428b30072a635af4ac0908fa5abeb0160e853d9f21611485b78548e5c8816791
- Size of remote file:
- 167 MB
- SHA256:
- f4c27c8d40b9938cbcb03978ab4afe14efa8d1eb6279fff3cab9f3c5dde354bd
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