Illustrious Lightweight Realistic Image Generation ModelThis is an optimized version of an illustrious image generation model, with a focus on realism and speed while still maintaining high-quality results. The primary goal was to create a lightweight, fast-running model that can run efficiently even on low VRAM devices.The key modifications include:<ul><li>Integration of the DMD2 LoRA adapter</li><li>Reduction in UNET precision to 8-bit</li><li>Lowered generation steps down to only 4-8</li></ul>In testing, I've found that optimal generation parameters are as follows (tested on an M2 MacBook Air with 8GB RAM):<ul><li>Steps: 4-8</li><li>CFG Scale: 1.0 - 1.2</li><li>Sampler: LCM</li><li>Scheduler: Polyexponential</li><li>Upscaler: Foolhardy_Remacri at 2x scale</li><li>Denoising Strength: 0.4 - 0.8</li></ul>Please note that the final image size will be generated from a 512x512, 512x768, etc, base for 4-8 steps with a 2x upscale to achieve a 1024x1024, 1024x1536 resolution output.This model can be run using Automatic1111 or Forge.For best results, ensure your system meets the minimum requirements:<ul><li>CPU with at least 8GB RAM</li><li>GPU with low 8GB VRAM (this model is optimized to reduce VRAM usage) </li></ul>NOTE: does tend to be NSFW, so beware. <img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9f431194-42f5-4811-a267-0c68d06c6f95/width=525/9f431194-42f5-4811-a267-0c68d06c6f95.jpeg" />Possible upcoming NatVis merge, still in experimental phase...

ReallyIllustrious

The key modifications include:<ul><li>Integration of the DMD2 LoRA adapter</li></ul>This version's more for people who want to try merges with other models. It's not optimised for low VRAM machines, just for speed.

reallyillustrious_fp16.safetensors

FP16

DMD2-NSFW

Base

DMD2

Illustrious Lightweight Realistic Image Generation ModelThis is an optimized version of an illustrious image generation model, with a focus on realism and speed while still maintaining high-quality results. The primary goal was to create a lightweight, fast-running model that can run efficiently even on low VRAM devices.The key modifications include:<ul><li>Integration of the DMD2 LoRA adapter</li><li>Reduction in UNET precision to 8-bit</li><li>Lowered generation steps down to only 4-8</li></ul>In testing, I've found that optimal generation parameters are as follows (tested on an M2 MacBook Air with 8GB RAM):<ul><li>Steps: 4-8</li><li>CFG Scale: 1.0 - 1.2</li><li>Sampler: LCM</li><li>Scheduler: Polyexponential</li><li>Upscaler: Foolhardy_Remacri at 2x scale</li><li>Denoising Strength: 0.4 - 0.8</li></ul>Please note that the final image size will be generated from a 512x512, 512x768, etc, base for 4-8 steps with a 2x upscale to achieve a 1024x1024, 1024x1536 resolution output.This model can be run using Automatic1111 or Forge.For best results, ensure your system meets the minimum requirements:<ul><li>CPU with at least 8GB RAM</li><li>GPU with low 8GB VRAM (this model is optimized to reduce VRAM usage)</li></ul>NOTE: does tend to be NSFW, so beware.

Files with SHA256: 18bf863457f3e9c02ab398337687323abe5f93f6aa639a647350ed8f4259189b