Instructions to use machinelearningzuu/queue_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use machinelearningzuu/queue_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="machinelearningzuu/queue_detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("machinelearningzuu/queue_detection") model = AutoModelForObjectDetection.from_pretrained("machinelearningzuu/queue_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee9d190cfc2fcf6ba31c57b5f6ad39b7d740df9a7f75a1aa22574e44f8609682
- Size of remote file:
- 5.11 kB
- SHA256:
- 6544c72c5618fc831bdc68dafcee3d41114f9349d5b6278e35800b80cce223cc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.