from transformers import ViTFeatureExtractor, ViTForImageClassification
from PIL import Image
import torch

model_name = "saved_model"

model = ViTForImageClassification.from_pretrained(model_name)
feature_extractor = ViTFeatureExtractor.from_pretrained(model_name)

model.eval()

image_path = '/path/'
image = Image.open(image_path).convert('RGB')

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

with torch.no_grad():
    outputs = model(**inputs)
    logits = outputs.logits

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

classes = model.config.id2label

print(f"Predicted class: {classes[predicted_class_idx]}")