# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("pawlo2013/kimchi-classification")
model = AutoModelForImageClassification.from_pretrained("pawlo2013/kimchi-classification")Quick Links
Although it's unlikely you'll ever use it, This model was trained for classifying different types of kimchi (Korean cabbage). It achieved 89% accuracy on a test set comprising of 11 different classes of this Korean delicacy.
labels_eng = ['baechu', 'baik', 'boochoo', 'chongkak', 'got', 'kkakdoogi', 'moosaengchae', 'nabak', 'ohyeesobaki', 'pa', 'yeolmoo']
labels_kr = ['배추', '백(대파)', '부추', '총각김치', '고추', '깍두기', '무생채', '나박', '오이소박이', '파', '열무']
This model is basically a fintuned version of the vision tranformer .
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pawlo2013/kimchi-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")