SwinV2-Large Classifier (384x384, Jet-Colored Gradients)

This model is a SwinV2-Large (384x384) vision transformer trained for image classification on Jet-colored gradient maps. The model learns to identify visual patterns in synthetic or colormap-encoded data to be suitable for detecting GAN generated images.

🧩 Model Details

Architecture: SwinV2-Large (384x384 input resolution)
Framework: PyTorch
Training Data: Jet-colored gradients (Mukhbir dataset on kaggle)
Use case: Classification of Real or Fake(Gan)

🛠️ How to Use

from huggingface_hub import hf_hub_download
import torch

# Download the model
model_path = hf_hub_download(repo_id="mukhbiir/Swin_Classifier", filename="model.pt")
model = torch.load(model_path)
model.eval()