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
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("lamnt2008/car_brands_classification")
model = AutoModelForImageClassification.from_pretrained("lamnt2008/car_brands_classification")Quick Links
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Model tree for lamnt2008/car_brands_classification
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k
# 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")