Instructions to use beingamit99/car_damage_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beingamit99/car_damage_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="beingamit99/car_damage_detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("beingamit99/car_damage_detection") model = AutoModelForImageClassification.from_pretrained("beingamit99/car_damage_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80e690182ed09347cd899dd0b6bd5f059e0a96726f78a003b889987951bb35ac
- Size of remote file:
- 14.2 kB
- SHA256:
- 27b3f5da84362263ada750e9677e6134c3138b0a57517e2c0599b62de2913cf9
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