Instructions to use ArrayDice/Vehicle_Detection_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArrayDice/Vehicle_Detection_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ArrayDice/Vehicle_Detection_Model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ArrayDice/Vehicle_Detection_Model") model = AutoModelForObjectDetection.from_pretrained("ArrayDice/Vehicle_Detection_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5ed4112683f72562a317657221094696f28b9563fed3d6cb07794bf7d5946ac
- Size of remote file:
- 167 MB
- SHA256:
- 1e45faf0f071fe3c5992867f6904f8273144becdc068ff6928c9093947239c93
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