Paragon_V1.0
| Property | Value |
|---|---|
| License | CreativeML OpenRAIL-M |
| Author | SG161222 |
| Framework | Diffusers |
| Model Type | Text-to-Image |
What is Paragon_V1.0?
Paragon_V1.0 is a sophisticated text-to-image generation model that comes with an integrated VAE (Variational Autoencoder). Currently in its testing phase, this model is designed to produce high-quality images while maintaining anatomical accuracy and realistic details.
Implementation Details
The model utilizes the StableDiffusionPipeline architecture and is optimized for specific generation parameters. It employs Safetensors for model weight storage and includes built-in support for inference endpoints.
- Recommended sampling method: Euler A
- Optimal CFG Scale: 5-12
- Clip Skip: 2
- Integrated VAE architecture
Core Capabilities
- High-fidelity image generation with anatomical accuracy
- Built-in VAE for enhanced image quality
- Supports Hires.Fix with configurable parameters
- Comprehensive negative prompt handling for artifact reduction
- Flexible upscaling options with customizable denoising strength
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its integrated VAE and specific optimization for anatomical accuracy, with built-in safeguards against common generation artifacts through comprehensive negative prompting.
Q: What are the recommended use cases?
The model excels at generating realistic images with particular attention to anatomical correctness. It's especially suitable for high-resolution image generation using Hires.Fix with recommended denoising strength of 0.35-0.7 and upscaling ratios of 1.1-2.0.
