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_11-43-31_mcity-rtx-4090 /events.out.tfevents.1739378611.mcity-rtx-4090.1808996.0
- Xet hash:
- 93e04f98d24aa5a9cbc7a2d204cf395d71eda5a24a16ae39b66a5e7a656b29a1
- Size of remote file:
- 6.16 kB
- SHA256:
- fb765ffa2790d67dcbe573696abf535d2e92054a84b1a95bde5d78323c57248f
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