Get example image from official fairface repo + read it in as an image

r = requests.get('https://github.com/dchen236/FairFace/blob/master/detected_faces/race_Asian_face0.jpg?raw=true') im = Image.open(BytesIO(r.content))

Init model, transforms

model = ViTForImageClassification.from_pretrained('nateraw/vit-age-classifier') transforms = ViTFeatureExtractor.from_pretrained('nateraw/vit-age-classifier')

Transform our image and pass it through the model

inputs = transforms(im, return_tensors='pt') output = model(**inputs)

Predicted Class probabilities

proba = output.logits.softmax(1)

Predicted Classes

preds = proba.argmax(1)