A Guide to Negative Prompts in Stable Diffusion

Negative prompts are a crucial feature in Stable Diffusion, a text-to-image generation model. They work alongside positive prompts to guide the model towards generating images that align with the user's vision. By using negative prompts, users can eliminate unwanted elements from their output and achieve more precise results. This technique also offers greater creative control and saves time by reducing the need for extensive post-processing. To effectively use negative prompts in Stable Diffusion, users should identify unwanted elements, craft clear prompts, combine them with positive prompts, iterate and refine their inputs, and be specific while avoiding overloading the model with too many negative prompts.