Added 5 production-ready workflows to leverage downloaded CivitAI NSFW models: **NSFW Text-to-Image Workflows (3):** - lustify-realistic-t2i-production-v1.json - Photorealistic NSFW with LUSTIFY v7.0 - DPM++ 2M SDE, Exponential scheduler, 30 steps, CFG 6.0 - Optimized for women in realistic scenarios with professional photography quality - pony-anime-t2i-production-v1.json - Anime/cartoon/furry with Pony Diffusion V6 XL - Euler Ancestral, Normal scheduler, 35 steps, CFG 7.5 - Danbooru tag support, balanced safe/questionable/explicit content - realvisxl-lightning-t2i-production-v1.json - Ultra-fast photorealistic with RealVisXL V5.0 Lightning - DPM++ SDE Karras, 6 steps (vs 30+), CFG 2.0 - 4-6 step generation for rapid high-quality output **Enhancement Workflows (2):** - lora-fusion-t2i-production-v1.json - Multi-LoRA stacking (text-to-image directory) - Stack up to 3 LoRAs with adjustable weights (0.2-1.0) - Compatible with all SDXL checkpoints including NSFW models - Hierarchical strength control for style mixing and enhancement - nsfw-ultimate-upscale-production-v1.json - Professional 2x upscaling with LUSTIFY - RealESRGAN_x2 + diffusion refinement via Ultimate SD Upscale - Tiled processing, optimized for detailed skin texture - Denoise 0.25 preserves original composition **Documentation:** - Comprehensive README.md with usage examples, API integration, model comparison - Optimized settings for each workflow based on model recommendations - Advanced usage guide for LoRA stacking and upscaling pipelines - Version history tracking **Total additions:** 1,768 lines across 6 files These workflows complement the 27GB of CivitAI NSFW models downloaded in previous commit. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
264 lines
6.1 KiB
JSON
264 lines
6.1 KiB
JSON
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"name": "RealVisXL V5.0 Lightning Fast NSFW Text-to-Image",
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"version": "1.0",
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"description": "Production workflow for RealVisXL V5.0 Lightning checkpoint optimized for ultra-fast photorealistic NSFW generation with 4-6 step inference (vs 30+ for standard models)",
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