Instructions to use lamnt2008/car_brands_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lamnt2008/car_brands_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lamnt2008/car_brands_classification") 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("lamnt2008/car_brands_classification") model = AutoModelForImageClassification.from_pretrained("lamnt2008/car_brands_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f01f8cbb7013509324e332b386cf4da2a7a7ad6861b876be02989cf9ec5a3db
- Size of remote file:
- 347 MB
- SHA256:
- ef8b56e80889d98565cca5bf3610951f672e183b50ac0e4a2272ad728001c962
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