sdxl-vae
by stabilityai
--- license: mit tags: - stable-diffusion - stable-diffusion-diffusers inference: false --- You can integrate this fine-tuned VAE decoder to your existing workf
🧠 Architecture Explorer
Neural network architecture
About
You can integrate this fine-tuned VAE decoder to your existing workflows, by including a argument to the SDXL is a latent diffusion model, where the diffusion operates in a pretrained, learned (and fixed) latent space of an autoencoder. While the bulk of the semantic composition is done by the latent diffusion model, we can improve _local_, high-frequency details in generated images by improving the qu...
📝 Limitations & Considerations
- • Benchmark scores may vary based on evaluation methodology and hardware configuration.
- • VRAM requirements are estimates; actual usage depends on quantization and batch size.
- • FNI scores are relative rankings and may change as new models are added.
- • Data source: [{"source_platform":"huggingface","source_url":"https://huggingface.co/stabilityai/sdxl-vae","fetched_at":"2025-12-19T07:41:01.179Z","adapter_version":"3.2.0"}]
📚 Related Resources
📄 Related Papers
No related papers linked yet. Check the model's official documentation for research papers.
📊 Training Datasets
Training data information not available. Refer to the original model card for details.
🔗 Related Models
Data unavailable