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 /Feb07_10-00-59_mcity-rtx-4090 /events.out.tfevents.1738940459.mcity-rtx-4090.206624.0
- Xet hash:
- aa796b024abfd437a68e900a8c3d9b10ceeb0ecf85a2e30cc592bf5728999d74
- Size of remote file:
- 48.9 kB
- SHA256:
- 43cf1fa6bba482989ce68cc10b4a1c8a23a6846e10d61c471e7558bfa20f812c
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