StyleGAN2 Discriminator (FFHQ, NVIDIA)

This model is the discriminator component of StyleGAN2, based on the original architecture introduced by NVIDIA and trained on the FFHQ dataset. The model is designed to distinguish between real and fake images, and is typically used in generative adversarial networks (GANs) for high-resolution face synthesis.

🧩 Model Details

Architecture: StyleGAN2 Discriminator (NVIDIA)
Framework: PyTorch
Trained on: FFHQ (Flickr-Faces-HQ)
Use case: Discriminator in GAN training or standalone real/fake image classification

🛠️ How to Use

from huggingface_hub import hf_hub_download
import torch

# Download the model
model_path = hf_hub_download(repo_id="mukhbiir/StyleGAN2_Discriminator", filename="model.pt")
model = torch.load(model_path)
model.eval()

📚 References StyleGAN2: Karras, Tero, et al. "Analyzing and improving the image quality of StyleGAN." CVPR 2020. Paper link | NVIDIA GitHub

FFHQ Dataset: https://github.com/NVlabs/ffhq-dataset