model.py

import torch , torchvision

from torch import nn

def create_vit_model(num_classes:int=3, seed:int=42):

  weights = torchvision.models.ViT_B_16_Weights.DEFAULT
  transforms = weights.transforms()
  model = torchvision.models.vit_b_16(weights= weights)

  for param in model.parameters():
    param.requires_grad = False

  model.classifier = nn.Sequential(
        nn.Dropout(p=0.3, inplace=True),
        nn.Linear(in_features=1408, out_features=num_classes)
  )

  return model , transforms