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πŸ“‘ Reference Library β€’ Updated for 2026 Releases

AI Parameter & Syntax Cheat Sheet

Everything you need to master Midjourney flags, Kling AI video camera vectors, and LLM hyperparameters in one clean reference.

🎨 Midjourney v6.1 Flags & Parameters

v6.1 Standard
--ar <ratio> Aspect Ratio

Sets the width-to-height ratio of the canvas.

Examples:
--stylize <0-1000> (or --s) Stylize Strength

Controls how strongly Midjourney applies its artistic aesthetic.

Examples:
--chaos <0-100> (or --c) Chaos & Variety

Determines how varied and unexpected the initial 4 image grid results are.

Examples:
--weird <0-3000> (or --w) Weirdness Factor

Introduces bizarre, quirky, and avant-garde visual elements.

Examples:
--no <items> Negative Prompting

Tells the model what objects, artifacts, or styles to remove from the render.

Examples:
--tile Seamless Texture Pattern

Generates seamless repeating tiles for textiles, wallpapers, and game textures.

Examples:
--sref <url> Style Reference

Applies the aesthetic, color grading, and texture from a reference image URL.

Examples:
--cref <url> Character Reference

Maintains facial features and clothing consistency of a specific character across scenes.

Examples:

🎬 AI Video Camera Movements (Kling AI & Runway)

Precision kinetic tokens to control 3D camera trajectory without distortion.

FPV Racing Drone Dive Kling AI / Runway

"FPV racing drone diving smoothly downwards, orbiting 180 degrees around subject, dynamic speed ramp."

Vertigo Dolly-Zoom (Hitchcock Zoom) Runway Gen-3

"Continuous camera dolly zoom in while background perspective dramatically widens, maintaining sharp focal center."

Whip Pan Transition Kling AI / Luma

"High-speed horizontal whip pan transitioning from interior living room into golden hour mountain vista with motion blur."

Continuous Orbital Tracking Kling AI

"Smooth circular orbital camera movement around subject at steady velocity, shallow depth of field, 24fps motion blur."

πŸ€– LLM Hyperparameters (ChatGPT, Claude, DeepSeek)

Temperature (0.0 to 2.0)

Controls randomness. Lower values are deterministic and precise; higher values increase linguistic creativity.

Tuning: 0.2 for Code/Data, 0.7 for Marketing, 1.2 for Brainstorming

Top-P (Nucleus Sampling, 0.0 to 1.0)

Dynamically limits token candidates to those with cumulative probability P. Keep temperature at 1.0 when tuning Top-P.

Tuning: 0.9 (Default standard)

System Prompt vs. User Prompt

System messages establish non-negotiable boundaries, negative rules, and output schemas that survive long chats.

Tuning: System: Role & Constraints | User: Specific Task
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