Instructions to use mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50") model = AutoModelForObjectDetection.from_pretrained("mcity-data-engine/fisheye8k_microsoft_conditional-detr-resnet-50") - Notebooks
- Google Colab
- Kaggle
fisheye8k_microsoft_conditional-detr-resnet-50 / runs /Feb12_13-08-31_mcity-rtx-4090 /events.out.tfevents.1739383712.mcity-rtx-4090.1868198.0
- Xet hash:
- 8ddf2182e8d156054142ad8b171f6c4769d7f7c1531eb32fbcce175918c2b8e1
- Size of remote file:
- 6.77 kB
- SHA256:
- 8aafbcd5294335220893ed21f67dfa3236fa8a7f1bd1cf41b83ec99f23c66548
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