Exhaustive guide to negative prompts covering common negative terms, negative embeddings (EasyNegative, bad_prompt), weighting strategies, model-specific negative prompts, and common mistakes like over-weighting.
Negative Prompts Complete Guide: **Universal Negatives**: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry **Negative Embeddings**: - EasyNegative: All-purpose negative embedding - bad_prompt_version2: Reduces common artifacts - ng_deepnegative_v1_75t: Deep negative for realistic models **Weighting Strategy**: - Start with universal negatives at weight 1.0 - Add specific fixes: (bad hands:1.4), (deformed fingers:1.3) - Avoid over-weighting (>2.0) — causes inverse artifacts **Model-Specific**: - Realistic models: Add "cartoon, anime, illustration" to negatives - Anime models: Add "photorealistic, 3d render" to negatives - SDXL: Negative prompts less critical but still useful
Start with universal negatives, then add specific fixes based on artifacts you see. Use negative embeddings for broad quality improvement.
Design and optimize ComfyUI node workflows for Stable Diffusion. Covers ControlNet, IP-Adapter, inpainting, upscaling, and multi-pass generation pipelines.
Generate stunning photorealistic portraits with SDXL. Covers lighting setups, camera simulation, skin texture, and professional photography techniques.
Technical deep-dive into prompt engineering covering token limits, attention mechanisms, prompt weighting with parentheses and numerical values, embedding manipulation, and A/B testing different prompt structures with reproducible experiments.
Covers the full prompt engineering workflow including subject specification, style references, quality boosters, camera and lighting terminology, negative prompt strategies, and CFG scale tuning for different prompt styles.
Official Hugging Face documentation on prompt weighting techniques in the Diffusers library, covering Compel syntax, numerical weights, blend operations, and conjunction prompts for advanced control over generation.
Curated GitHub Gist with copy-paste SDXL prompt examples organized by category (portraits, landscapes, sci-fi, fantasy, product photography) with specific quality modifiers and style keywords tested on SDXL.
Workflows from the Neura Market marketplace related to this Stable Diffusion resource