
from transformers import AutoImageProcessor, SwinForImageClassification

from PIL import Image

import requests

url = "http://images.cocodataset.org/val2017/000000039769.jpg"

image = Image.open(requests.get(url, stream=True).raw)


processor = AutoImageProcessor.from_pretrained("alicelouis/Swin2e-4Lion")

model = SwinForImageClassification.from_pretrained("alicelouis/Swin2e-4Lion")

inputs = processor(images=image, return_tensors="pt")

outputs = model(**inputs)

logits = outputs.logits

# model predicts one of the 1000 ImageNet classes

predicted_class_idx = logits.argmax(-1).item()

print("Predicted class:", model.config.id2label[predicted_class_idx])

adenocarcinoma large.cell normal squamous.cell