# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("Nahrawy/AIorNot")
model = AutoModelForImageClassification.from_pretrained("Nahrawy/AIorNot")Quick Links
Classification model used to classify real images and AI generated images.
The model used is swin-tiny-patch4-window7-224 finetued on aiornot dataset.
To use the model
import torch
from transformers import AutoFeatureExtractor, AutoModelForImageClassification
labels = ["Real", "AI"]
feature_extractor = AutoFeatureExtractor.from_pretrained("Nahrawy/AIorNot")
model = AutoModelForImageClassification.from_pretrained("Nahrawy/AIorNot")
input = feature_extractor(image, return_tensors="pt")
with torch.no_grad():
outputs = model(**input)
logits = outputs.logits
prediction = logits.argmax(-1).item()
label = labels[prediction]
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nahrawy/AIorNot") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")