Stable Diffusion Prompt Guide, How Long Can a Prompt Be?
by Rajalaxmi
Updated Apr 07, 2023
Stable Diffusion
Stable Diffusion, a revolutionary deep learning, text-to-image model, was unveiled in 2022 by start-up Stability AI in collaboration with academic researchers and non-profit organizations. This remarkable technology generates highly detailed images based on text descriptions and can also be utilized for tasks like inpainting, outpainting, and image-to-image translations guided by text prompts.
Stable Diffusion belongs to the family of latent diffusion models, a type of deep generative neural network that has the capability to generate complex images from textual input. Unlike previous proprietary text-to-image models such as DALL-E and Midjourney, which were accessible only through cloud services, Stable Diffusion's code and model weights have been made publicly available. Furthermore, the model can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM, making it more accessible to the masses.
This breakthrough technology has opened up numerous possibilities for industries such as advertising, film, and gaming, where detailed images are crucial in communicating ideas and concepts. It can also be used in various scientific and medical fields, where it can aid in creating highly detailed visualizations of complex data sets.
Stable Diffusion Prompt Guide
1. Subject
The subject is the primary focus of the image. To create a successful prompt, be specific about what you want to see in the image. It's important to provide enough information about the subject to ensure that the resulting image matches your vision.
2. Medium
The medium refers to the materials used to create the artwork, such as oil paint, charcoal, or digital rendering. Each medium has its own unique characteristics that can significantly impact the style and mood of the image. Consider the medium you want to be used when creating your prompt.
3. Style
The style of the image is the artistic approach taken by the artist. Styles can range from impressionism to realism and beyond. It's essential to be specific about the style you want to see in the image.
4. Artist
Artist names are powerful modifiers that can help you achieve the desired style. Using a specific artist's name as a reference can help dial in the exact style you're looking for. It's also possible to blend multiple artists' styles.
5. Website
Niche graphic websites such as Artstation and Deviant Art are excellent sources of inspiration for different genres. By using them in your prompt, you can guide the image toward a particular style or genre.
6. Resolution
The resolution of the image refers to its sharpness and detail. If you want a highly detailed image, make sure to include specific keywords to communicate that in the prompt.
7. Additional details
Additional details can modify the image further to create a more specific mood or atmosphere. For example, adding keywords such as sci-fi or dystopian can significantly impact the resulting image.
8. Color
Colors have a significant impact on the mood and tone of an image. To control the overall color scheme, include specific keywords in your prompt to ensure that the resulting image aligns with your vision.
9. Lighting
Lighting can make or break an image. It's crucial to consider the type of lighting you want to see in the image and include specific keywords to ensure that the image meets your expectations.
How Long Can a Prompt Be?
When using Stable Diffusion, a powerful language model developed by OpenAI, there are certain limitations you should be aware of. One of these limitations has to do with the number of keywords you can use in the prompt.
The basic version of Stable Diffusion, known as Stable Diffusion v1, has a limit of 75 tokens for the prompt. It's important to note that tokens are not the same as words. The model uses a process called tokenization to convert the prompt into a numerical representation of words it understands. This means that if you enter a word that the model is not familiar with, it will break it up into two or more sub-words until it can identify it.
For example, let's say you wanted to use the keyword "dream beach" in your prompt. This is not a word that Stable Diffusion recognizes, so it would break it up into two tokens: "dream" and "beach". Each of these tokens is represented as a number that the model can understand.
It's important to keep this token limit in mind when using Stable Diffusion, as exceeding it can lead to poor results or errors. However, different versions of Stable Diffusion may have different token limits, so it's always a good idea to check the documentation or contact the support team for guidance.
Stable Diffusion Prompt Examples
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The Stable Diffusion prompt generates a bizarre and unexpected scenario of Pope Francis wearing a leather jacket and being a DJ in a nightclub. The image is described as a masterpiece with a giant mixing table and 4k resolution. However, the negative prompt presents a contrasting image of a poorly drawn, grainy, and low-res white robe, with extra and missing limbs, and blurry, malformed hands. The parameters used for this prompt include 40 steps, DDIM sampler, CFG scale of 8.0, seed 1639299662, face restoration, and a size of 480x512.
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In this Stable Diffusion prompt, Luke Skywalker is portrayed as ordering a burger and fries from the Death Star canteen. The parameters used in this prompt include 50 steps, Euler a sampler, CFG scale of 7.0, seed 2551426893, and a size of 512x512.
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The Stable Diffusion prompt generates a portrait of a cute Anime black girl with a fine and realistic shaded face, fine details, and cute freckles. The lighting is described as being by Ilya Kuvshinov, Giuseppe Dangelico, Pino and Michael Garmash, and Rob Rey, with the image being a masterpiece. The parameters used in this prompt include 29 steps, Euler a sampler, CFG scale of 8.0, seed 3873181273, and a size of 320x512.
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This Stable Diffusion prompt generates an image of a cute small cat sitting in a movie theater, eating chicken wings, and watching a movie. The image is described as being detailed, with cozy indoor lighting, and a cinematic character design by Mark Ryden, Pixar, and Hayao Miyazaki. The prompt uses the Unreal engine, Daz, and Octane render, resulting in a hyper-realistic digital painting. However, the negative prompt presents an image of ugly arms and hands. The parameters used in this prompt include 25 steps, Euler a sampler, CFG scale of 8.0, seed 3099373267, and a size of 512x512.
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Similarly, this Stable Diffusion prompt generates an image of a cute small dog sitting in a movie theater, eating popcorn, and watching a movie. The image is described as being detailed, with cozy indoor lighting, and a cinematic character design by Mark Ryden, Pixar, and Hayao Miyazaki. The prompt uses the Unreal engine, Daz, and Octane render, resulting in a hyper-realistic digital painting. However, the negative prompt presents an image of ugly arms and hands. The parameters used in this prompt include 25 steps, Euler a sampler, CFG scale of 8.0, seed 2470332296, and a size of 512x512.
Stable Diffusion prompt guide - FAQs
Stable Diffusion is a deep learning, text-to-image model released in 2022. It is primarily used to generate detailed images based on text descriptions, although it can also be applied to other tasks such as inpainting, outpainting, and image-to-image translations guided by a text prompt.
Stable Diffusion is a type of deep generative neural network known as a latent diffusion model. It uses a process called diffusion to generate complex images from textual input. The model is trained on a large dataset of image-text pairs, and it learns to associate specific textual descriptions with corresponding images.
Stable Diffusion can be used in various industries such as advertising, film, and gaming, where highly detailed images are crucial in communicating ideas and concepts. It can also be used in scientific and medical fields to create highly detailed visualizations of complex data sets.
Yes, Stable Diffusion's code and model weights have been released publicly, making it accessible to everyone. Additionally, it can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM, making it more accessible to a wider audience.
Stable Diffusion represents a significant advancement in text-to-image models, as it can generate highly detailed images with greater fidelity and realism than previous models. Additionally, its accessibility and ease of use make it a game-changer in the field of generative models.