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from transformers import ViTConfig, ViTForImageClassification
from transformers import ViTFeatureExtractor
from PIL import Image
import requests
import matplotlib.pyplot as plt
import gradio as gr
# option 1: load with randomly initialized weights (train from scratch)
config = ViTConfig(num_hidden_layers=12, hidden_size=768)
model = ViTForImageClassification(config)
print(config)
feature_extractor = ViTFeatureExtractor()
# or, to load one that corresponds to a checkpoint on the hub:
#feature_extractor = ViTFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
image = "cats.jpg"
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