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.1738946477.mcity-rtx-4090.206624.1
- Xet hash:
- 3fc5b498fa024c962422832ac04bff15cc1ef6eac8ffb6201bb7ac4ea779422b
- Size of remote file:
- 364 Bytes
- SHA256:
- b606393f5564aa3115927a0de50bb5368ac575b2022c24cc507da37b05cc5129
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