dorarad/gansformer

Health v2 · maintenance only

Adoption not part of the score

1344 stars · 152 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

GANformer is a research implementation of a generative adversarial transformer that uses a bipartite attention structure for efficient high-resolution image generation. It supports both PyTorch and TensorFlow and generalizes StyleGAN with multiplicative region-based modulation to encourage compositional scene representations.

Use cases

• generate images with a transformer-based GAN
• train a GAN on custom image datasets
• experiment with compositional scene generation
• sample images from pretrained GANformer models
• research attention-based generative adversarial networks
• compare against StyleGAN architectures

When to choose

• you need a research-grade GAN with transformer attention for image synthesis
• you want to study compositional and region-based generative modeling
• you want pretrained models for image generation experiments

When to avoid

• you need a production image-generation service with active support
• you require the latest GPU stack since the code targets older PyTorch/TensorFlow and CUDA versions
• you want a simple off-the-shelf text-to-image generator

Facets

library · maturity maintenance

machine-learning deep-learning image-processing graphics machine-learning deep-learning computer-vision image-processing python gan transformer generative-models stylegan image-synthesis research-code pytorch tensorflow gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="dorarad/gansformer")