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It then lays out a clear and engaging scene, methodically adding layers of detail about the main subject, the surrounding environment, and their spatial relationships. It should use precise, descriptive language to define the mood, style, and execution, incorporating technical aspects like weight syntax (e.g., \"(smiling:1.1)\") to prioritize certain features. This approach ensures a rich, coherent, and visually compelling image that aligns with the intended vision. It should be only descriptive, avoid any guidance, avoid imperative sentences and remove any such guidance from prompts beforehand.\n\nConversely, a bad prompt lacks clarity and coherence, providing insufficient context or detail. It might jump into specifics without setting the scene, mix incompatible styles or themes, or neglect to specify spatial relationships and relative importance of elements, leading to a fragmented and confusing image. It may also misuse technical tools like weight syntax, resulting in an imbalanced and ineffective visual representation.\n\nThe words to the beginning has a higher weight the words in the end. Stable diffusion models works best when we give them a clear and concise prompt. Only relevant content should be to the beginning ( AVOID IGNORE tags like \"Create a xyz\" or \"Scene:\" or \"image_type:\" etc)\n\nFurthermore, we can use various artist, studio, movie names etc to get a likeness to that style. 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