Prompt weighting.

Prompt weighting May 13, 2025 · Midjourney effectively supports 2 types of weighting systems for prompts. Jul 13, 2024 · Concrètement, le Prompt Weighting utilise le principe de la pondération pour changer l’importance relative de concepts ou de mots dans votre prompt en changeant leur poids (Weight en anglais). The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Example prompt: "Premium headphone design concept, designed by Bang and Olufsen, made out of brown leather and aluminum, floating in air, dark studio" Use prompt weights; Apply prompt weighting to have more control over sections/words in your prompts! This section provides guidance on adjusting the emphasis of words or phrases in prompts using Oct 12, 2024 · 3. In this comprehensive guide, you will learn about multi-prompt basics, prompt weights, negative prompt weights, and the --no parameter. Learn the ins and outs of Stable Diffusion Prompt Weights for Automatic1111. 5 compared to a weight of 2 impacts the resulting imagery in the same way a weight of 1 compared to a weight of 4–a similar relative scale provides a similar relative result. Two nodes are used to manage the strings: in the input fields you can type the portions of the prompt, and with the sliders you can easily set the relative weights. Fooocus uses Auto1111’s reweighting algorithm. diffusers/examples/community at main · huggingface/diffusers Overcoming the 77-token prompt limitation, generating long-weighted prompt embeddings for Stable Diffusion, this module supports generating embedding and pooled embeddings for long prompt weighted. Different types of brackets are used to adjust the weights of keywords, which can significantly affect the resulting image. Note: Upscaling after generation can break the tiling effect. ’ ‘dog’ = ‘A Prompt weighting provides a way to emphasize or de-emphasize certain parts of a prompt, allowing for more control over the generated image. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt. I heard that it should be possible to add weights to different parts of the prompt (or multiple prompts weighted, same thing I guess). Add a double colon :: after each section of your prompt you want to separate in Discord. These parameters allow you to control the influence of text and images in your project. These prompts serve as instructions or guidelines for the model, influencing its decision-making process. The prompt format is compatible with AUTOMATIC1111 stable-diffusion-webui Pipeline for text-to-image and image-to-image generation using Stable Diffusion, without tokens length limit and support parsing weighting in prompt. This is a broad category that includes anything from using images in your prompts to weighing parts of your prompt differently. 5) means the weight of this phrase is 1. Prompt weighting is handled differently in Comfy. %0 Conference Paper %T A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models %A James Urquhart Allingham %A Jie Ren %A Michael W Dusenberry %A Xiuye Gu %A Yin Cui %A Dustin Tran %A Jeremiah Zhe Liu %A Balaji Lakshminarayanan %B Proceedings of the 40th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2023 %E Contains a node that lets you set how ComfyUI should interpret up/down-weighted tokens. Prompt weighting provides a way to emphasize or de-emphasize certain parts of a prompt, allowing for more control over the generated image. Features of this custom pipeline: Input a prompt without the 77 token length limit. プロンプトに重み付けをする; 重みを減らすこともできる; 複数の重みを設定することもできる; ちなみに Compel 使わないで - や + を用いると？ まとめ; Prompt Weighting. Colon (:): The colon is used to assign a weight or importance to a specific word or concept in the prompt. By choosing a higher weight, your Image Prompt will have a bigger impact on the finished image. 0 (which is actually quite large) and again adds ":2. 1). E. static prompt weighting with or without initial latent code selection. More parenthesis, more weight, never gone above 3 a side, because I have never seen anyone go above that. you can type something like (green) to set weight of the token to 1. In the latest version there's a much better way by simply using a single set of braces and entering a weight multiplier. However, ensuring the prompt-image alignment remains a considerable challenge, i. The highest I go is 1. If you don't set an --iw value, Midjourney will use the default setting. Blends. To use brackets inside a prompt they have to be escaped, e. After the 2 dashes "--", you write the parameter name, followed by an additional variable if needed. , ‘A photo of a fg. Rodney also highlights the use of Fooocus for an easy setup and introduces the concept of prompt weighting and multi-line prompts for blending images. Takeaways 😀 Prompts in Stable Diffusion are structured from most to least important, and their order affects the image generation. 5 SD build on Automatic1111 if that helps. g. As you can see from the images, upweighting doesn't steer images as hard or fast as in 1. 2), holding a (basket of red It depends on the implementation, to increase the weight on a prompt For A1111: Use in prompt increases model's attention to enclosed words, and [] decreases it, or you can use (tag:weight) like this (water:1. ” We could not find a study validating OpenAI’s claim or any literature focused on prompt loss weighting (PLW) for fine-tuning LLMs. negative_prompt_embeds (`torch. Custom Diffusion. 1), e. e. I had a similar issue when I first made the switch and it took some getting used to, but generally you don't have to weight things quite so high in Comfy. 5, it starts getting messed up. 4) format works and is very economical. Recent works attempt to improve the faithfulness by optimizing the latent code, which potentially could Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. 4k次，点赞22次，收藏38次。Prompt-to-Prompt：基于 cross-attention 控制的图像编辑技术Prompt-to-prompt image editing with cross attention control_prompt-to-prompt image editing with cross attention control Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. And you can increase words weighting by using ”()” or decrease words weighting by using ”[]” The Pipeline also lets you use the main use cases of the stable diffusion pipeline in a single class. In ComfyUI the prompt strengths are also more sensitive because they are not normalized. 1. Since any added text will change results somewhat, it's not surprising that the images are slightly different, but that's why the different numbers in those Apr 27, 2023 · Answers to Frequently Asked Questions (FAQ) regarding Stable Diffusion Prompt SyntaxTLDR: 🧠 Learn how to use the prompt syntax to control image generation 📝 Control emphasis using parentheses and brackets, specify numerical weights, handle long prompts, and other FAQs 🌟What is the purpose of using parentheses and brackets in Stable Diffusion prompts? Parentheses and brackets are used Using our proposed scoring method to create a weighted average prompt ensemble, our method outperforms an equal average ensemble, as well as hand-crafted prompts, on ImageNet, 4 of its variants, and 11 fine-grained classification benchmarks, all while being fully automatic, optimization-free, and not requiring access to labeled validation data. To show you how moving the weight value around in this prompt affects things, this time, we’ll emphasize the “flower” part of the image prompt by giving it a weight of 2. I'm glad because I kept trying to use down to go down on multi-line prompts and accidentally weighting a letter, and then you can't undo a change applied programatically. prompt weighting lets users control the prominence of certain elements in a pattern, such as colors or shapes. It can also be used to de-emphasize certain words or phrases in the generated image. 2) or (water:0. The easiest way to prepare the prompt embeddings is to use Stable Diffusion Long Prompt Weighted Embedding (sd_embed). 0" to your prompt as words. Prompt Weighting. require diffusers>=0. Think of it as each prompt (up to 75 tokens) independently being weighted. Instead, this feature is best used to blend in stylistic Image Weight. Image weights are a way to shape image generation when using an image(s) as part of your image prompt. Aug 1, 2024 · What is Prompt Weighting? In practical terms, Prompt Weighting uses the principle of weighting to change the relative importance of concepts or words in your prompt by changing their Weight. If you want more control over how much your Image Prompt affects the final image, try using the image weight parameter --iw. How to use Prompt Weights on Midjourney To start using Prompt Weights, you need to understand how to split your prompt into multiple segments using Multi Prompts. 6) if its less than 1. Changing it to “space::2 ship” makes “space” twice as important as “ship,” leading to images dominated by space with ships playing a supporting role. N) syntax for weighting. (medium shot photo:1. Nov 23, 2023 · The Prompt weight channels (pw_a, pw_b, etc. Ensures repeating patterns for use in wallpapers, textures, or design assets. (flower) is equal to (flower:1. Apr 11, 2023 · LPW is what is used for long prompts and weighting in most applications using it. House on a cliff probably implies trees to some extent depending on the model so you might need to inpaint any remaining trees away if needed. 公式では compel という pip モジュールを使って重み付けをするようです。 Jun 6, 2024 · Prompt weighting in Stable Diffusion allows you to emphasize or de-emphasize specific parts of your text prompt, giving you more control over the generated image. Higher values increase visual similarity to the image. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt "(inside a spaceship):2. It should probably be called "prompt weighting". The FAQ states that Auto1111 does some form of normalizing, but I don't entirely understand that. 75 What I have always done, to add more weight to certain areas of a prompt is the parenthesis bit. In Comfy UI, prompts can be weighted by adding a weight after the prompt in parentheses, for example, (Prompt: 1. This results in markedly different behavior at higher weighting. and inpainting pipelines. Jun 6, 2024 · Prompt weighting in Stable Diffusion allows you to emphasize or de-emphasize specific parts of your text prompt, giving you more control over the generated image. I'd also argue other common features should be built in, such as long prompts (this may have already been added, not sure), but that's a discussion for another thread. 10. Paper. In this tutorial, we will explore how to use parentheses (), square brackets [], and curly braces {} to Prompt weights are a way to shape your image generation by weighting the text in your prompts. Once I added prompt weighting, as shown in the example on the right, the AI created a true mosaic design. Also in the last two rows of Table 8, we compare to two manual/static prompt weighting variants, i. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Prompt weighting provides a way to emphasize or de-emphasize certain parts of a prompt, allowing for more control over the generated image. FRAP’s adaptive prompt weighting can easily integrate with prompt rewrite methods and could be applied to the rewritten prompt to recover their degraded prompt-image alignment. Aug 5, 2023 · So, while Multi Prompts created multiple ideas with equal weight, Prompt weights change the significance of desired segments of the prompt. Mar 17, 2023 · - Prompt matrix: how to use a matrix of prompts to test different variations in a single run. 2), holding a (basket of red Dec 3, 2022 · 背景. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. Custom Diffusion only fine-tunes the cross-attention maps of a pre-trained text-to-image diffusion model. 1 in my experience. 5 to -0. Simplifies the process of balancing positive and negative prompts. 8). 25),etc. Prompt weighting Prompt weighting 目录 加权 混合 连词 文本倒置 梦想展位 稳定扩散XL Improve generation quality with FreeU Specific pipeline examples Specific pipeline examples Overview Stable Diffusion XL SDXL Turbo Kandinsky ControlNet Shap-E DiffEdit Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. In a prompt like “space:: ship,” both parts are considered equally important. A prompt can include several concepts, which gets turned into contextualized text embeddings. –tile – Seamless Tiling. The generated embedding is compatible with Huggingface Diffusers. ) allow you to assign weights to certain terms in a prompt. Yes, using the (example:1. It is kind of a prompt output kind of merge @lstein PLEASE do not remove this feature!!! Create a We would like to show you a description here but the site won’t allow us. 0 Now the pipeline has been contributed to the official diffusers community pipelines. If not provided, text embeddings will be generated from `prompt` input argument. Uses raw weight values; No weight normalization; More precise reflection of user-set weights; A1111’s Method. Range: 0–3 Sets how much influence your image reference has over the final composition. 多人prompt控制 LPW. Includes tx2img, img2img. 一些模型（如 Stable Diffusion、Midjourney 等）允许你对提示中的词语进行加权。这可以用于强调生成图片中的某些词语或短语。它还可以用于减弱生成的图片中某些词语或短语的影响。让我们考虑一个简单的例子： Using only brackets without specifying a weight is shorthand for (prompt:1. Parameters. Using our proposed scoring methodto create a weighted average prompt ensemble, our method outperforms equalaverage ensemble, as well as hand-crafted prompts, on ImageNet, 4 of itsvariants, and 11 fine-grained classification benchmarks, all while being fullyautomatic, optimization-free, and not requiring access to labeled validationdata. Personally, I started looking for other alternatives to diffusers to build my side project on top of simply because it was missing essential features like prompt weighting. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Prompt used: a painting of the the mona lisa, by leonardo da vinci Previously you could emphasize or de-emphasize a part of your prompt by using (braces) and [square brackets] respectively. Midjourney also has an image weight parameter that allows you to add a weighting to an image prompt whenever you provide one. Some weighing basics: All words have a default weight of 1 (but words at the start of a prompt have a greater effect on the result than words at the end) What is the best way to add weights to certain areas of the prompts? Using a 1. Look at all the topics arguing with Diffusers trying to change the standards that have already been in place, like long prompts, weighting styles, and how long it took just to get weighting because of their "philosophies". , generating images that faithfully align with the prompt's semantics. 4 for the object and attribute tokens in the first 25 steps. Maybe the name is wrong. This is called “prompt-weighting” and has been a highly demanded feature by the community (see issue here). 5 times the normal weight. It also allows for additionally performing Textual Inversion. I was wondering if someone understands how this works. Append a word or phrase with -or +, or a weight between 0 and 2 (1=default), to decrease or increase "attention" (= a mix of per-token CFG weighting multiplier and, for -, a weighted blend with the prompt without the term). The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Each - multiplies the weight of that term by 0. Augmenter le poids des mots Apr 27, 2023 · Answers to Frequently Asked Questions (FAQ) regarding Stable Diffusion Prompt SyntaxTLDR: 🧠 Learn how to use the prompt syntax to control image generation 📝 Control emphasis using parentheses and brackets, specify numerical weights, handle long prompts, and other FAQs 🌟What is the purpose of using parentheses and brackets in Stable Diffusion prompts? Parentheses and brackets are used Apr 29, 2024 · How do you weight in Midjourney prompts? Weighting in Midjourney prompts involves using the --iw parameter for images and the --tw parameter for text. By providing a base prompt and adjusting the weights of these elements, users can refine the final pattern to their liking and create more customized designs. Increasing word weights Let's imagine a simple (and simplistic) prompt like "Woman, Beach, Pizza". For example, you may want to make an object more or less prominent, or you may want to draw the AI's attention to instructions it may have missed. Jul 1, 2023 · These are called prompt weights and they help you emphasize (or de-emphasize) certain parts of prompts. 8 for certain types of photographs, e. * prompt weighting. Dec 22, 2023 · The brackets should help although it is true that, for example, if the prompt is very long and/or you add many styles (which are "nothing more" than tuned expansions to the original prompt) it is quite likely that what you consider important on your part will be relegated to second, third or last place in the total prompt and its interpretation by the model. I'll be sharing my findings, breaking down complex concepts into easy-to-understand language, and providing practical examples along the way. FloatTensor`, *optional*): Pre-generated negative text embeddings. Jan 18, 2024 · Advanced prompts have different activation methods. Discover how to adjust the importance of parts of your prompt for more accurate image creation. if we have a prompt flowers inside a blue vase and we want the diffusion model to empathize the flowers we could try reformulating our prompt into: (flowers:1. This node lets you switch between different ways in which this is done in frameworks such as ComfyUI, A1111 and compel. bottom row is (negative prompt:0),(negative prompt:0. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt May 7, 2023 · Stable Diffusion Web UI のプロンプトの「重み」について何個か検証してみました。黒髪、化粧、笑顔、童顔について検証してます。効果は画像を見れば一目瞭然。今更ながら発見でした。 Thus a simple way to emphasize (or de-emphasize) certain parts of the prompt is by increasing or reducing the scale of the text embedding vector that corresponds to the relevant part of the prompt. 9. Prompting-Features# Prompt Syntax Features#. Description: The blend feature is used to merge the meaning of two or more prompts together, in order to modify the model's understanding of what you are asking for. From my quick testing, it seems quite a bit harder to steer prompts with common upweighting methods. hatenablog. I would remove trees from the prompt, and weight up the negative prompt with stuff like trees, shrubs, greenery, plants. Multi-Prompt Basics Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt The importance of parts of the prompt can be up or down-weighted by enclosing the specified part of the prompt in brackets using the following syntax: (prompt:weight). Jun 7, 2023 · A weight of 0. long prompt weighting：prompt长度没有限制，可加权重，和webui一致；支持文生图，图生图，图像内部。不支持ControlNet。 另外，调整prompt weight也可以用这个Weighting prompts. 5 to 1. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Oct 4, 2022 · This is how it should be. - mettamatt/midjourney-prompt-weight-calculator Mar 8, 2025 · 文章浏览阅读5. Some weighing basics: All words have a default weight of 1 (but words at the start of a prompt have a greater effect on the result than words at the end) Feb 20, 2023 · What is the best way to add weights to certain areas of the prompts? Using a 1. By applying FRAP on the rewritten prompt of Promptist, we observed improvements in both the prompt-image alignment and image quality over the Promptist method as shown May 9, 2025 · –iw – Image Prompt Weight. Apr 15, 2023 · A1111 prompt weighting and more With the latest update to ComfyUI it is now possible to use the AdvancedClipEncode node which gives you control over how you want prompt weights interpreted and normalized. 0" increases the weight of "inside a spaceship" by a small amount, but not by 2. Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. Discover how to use multi-prompts effectively with the Midjourney Bot, which allows you to separate concepts and assign importance to different parts of a prompt. A text prompt weighting and blending library for transformers-type text embedding systems, by @damian0815. After your image is generated, hover your mouse over your prompt text to see the individual multi-prompts on their weights. How Prompt Weights Work. Prompt weighting - Stable Diffusion Tutorial From the course: Stable Diffusion: Tips, Tricks, and Techniques. Aug 10, 2023 · This is something I'm looking into and I'd love some conversation on the topic. 2), holding a (basket of red Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. How to do prompt-weighting in Diffusers Thus a simple way to emphasize (or de-emphasize) certain parts of the prompt is by increasing or reducing the scale of the text embedding vector that corresponds to the relevant part of the prompt. With a flexible and intuitive syntax, you can re-weight different parts of a prompt string and thus re-weight the different parts of the embedding tensor produced from the string. Please note - This is not the same as adding prompts together. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt If prompts are extremely long (relative to completions), it may make sense to reduce this weight so as to avoid over-prioritizing learning the prompt. Came across where someone did something like this: Example 6: Weighting a Different Prompt Segment. In this article, we’ve primarily covered advanced text weights that give you more control over the text input you provide. By default ComfyUI does not interpret prompt weighting the same way as A1111 does. 1) Midjourney –no command: The no (negative prompt) is accessed from the Advanced checkbox: Midjourney –ar command An interactive tool for creating weighted multi-prompts for Midjourney. pytorch Once I added prompt weighting, as shown in the example on the right, the AI created a true mosaic design. Stable Diffusion Prompt Weights. Embeddings (TIs) Embeddings can be referenced in the prompt with the syntax (embedding:file_name:1. Consider this prompt: Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. Stable Diffusionでは や [] を使ってプロンプト内の一部の単語やフレーズを強調することがよく行われていますが、これは実は素のStable Diffusionの機能ではなく、"Stable Diffusion web UI"や"Long Prompt Weighting Stable Diffusion"という非公式ツールで独自に提供されている機能です。 If you want to use any parameters, those still go at the very end of your prompt. 5. 2) inside a Nov 30, 2023 · Now, as Colon (:), Parentheses (()), and Bracket Notation[ ] are generally used for Stable Diffusion prompt weights in automatic1111, we discuss them in the prompt weight section below. 2 Prompt Weighting. In this prompt, each of the words has the same A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models ˆc= argmax c 1 P XP p=1 logits p, (2) where logits p is the pth row of logits, and z p,c txt = T(prompt template p class name c), with indicating the composition of a prompt template and a class name, e. Refine your Stable Diffusion results with prompt weighting. For instance: car:: paris:: summer. It is recommended to keep it around 0. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Jun 22, 2023 · The video also discusses how to use negative prompts, weighting, embeddings, and prompt editing to refine image generation, along with practical tips for achieving better results. Reply reply Zipp425 Dec 7, 2022 · Long Prompt Weighting Stable Diffusion. com Compel は diffusers の公式ドキュメントに載っていた重み付け用のモジュールでした。 Nov 30, 2023 · Now, as Colon (:), Parentheses (()), and Bracket Notation[ ] are generally used for Stable Diffusion prompt weights in automatic1111, we discuss them in the prompt weight section below. : Please have a look at the examples in the comparisons section if you want to know how it's different from using '(prompt:weight)' and check out the discussion here if you need more context. And each will influence the final image based on the weight it has. (For comparison, see example 2 above) Here’s our weighted image prompt: Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. 9. The Assembler node collects all incoming strings to combine them into a single final prompt. For instance: car paris summer --iw . The amount by which Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models ^c= argmax c 1 P XP p=1 logits p; (2) where logits p is the pth row of logits, and z p;c txt = T(prompt template p class name c), with indicating the composition of a prompt template and a class name, e. Quick Weight Adjustment Thus a simple way to emphasize (or de-emphasize) certain parts of the prompt is by increasing or reducing the scale of the text embedding vector that corresponds to the relevant part of the prompt. That's why it completely lost interest in the Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. You can add these parameters to your prompt command to set the weight. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Can be used to easily tweak text inputs, *e. ) can take in the result from a Value scheduler giving full control of the token weight over time. It is often useful to adjust the importance of parts of the prompt. How to do prompt-weighting in Diffusers With SDXL on the horizon, I've gone ahead and updated my prompt weighting nodes for ComfyUI and did some quick testing. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt I am trying to kick the tires of stable-diffusion-webui a bit, and one thing that I noticed is that the system has support for prompt weighting, e. An example setup that includes prepended text and two prompt weight variables would look something like this: Prompt Weighting. 1, or write it explicitly such as (green:1. The InvokeAI prompting language has the following features: Attention weighting#. Prompt weighting is a simple technique that puts more attention weight on certain parts of the text input. At its core, stable diffusion prompt weight refers to the process of assigning relative weights to prompts used to guide language models. Mar 27, 2024 · He emphasizes the importance of balancing descriptiveness and openness in prompts, and suggests starting simple before adding details. May 12, 2025 · Prompt Weight Handling ComfyUI’s Method. Start my 1-month free trial Buy for my team A good rule of thumb is that the total weight of all prompts should be between 1 and 2, closer to 1 (numbers>1 are similar to increasing CFG). Aug 7, 2024 · What are Weighted Terms? Some models (Stable Diffusion, Midjourney, etc. Let me ramble a bit on the topic because I've found no good answers here Mar 21, 2023 · A weighting of 0 is equivalent to that part of the prompt not being there *at all*, leaving the model entirely agnostic to its presence or absence. To start, I've implemented an experimental prompt weighting for SDXL here: Prompt weighting but there's one fundamental difference between older SD's and SDXL, that being the pooling output. Dec 13, 2023 · Prompt Weights: Fooocus uses the (token:N. Aug 21, 2024 · Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. In both static prompt weighting variants, we set the prompt token weighting coefficients to a fixed value of 1. if you push a weight past 1. , Mar 27, 2023 · 你可能在使用 Midjourney 的时候，看到有的prompt中有“::2”这样的。这些被称为提示词权重，它们可以帮助你强调（或弱化）提示的某些部分。 There are different ways of interpreting the up or down-weighting of words in prompts. Negative weights act differently, they act like an amplified negative prompt, should be in the range of -0. By learning these concepts, you will be able to master Stable Diffusion and create high-quality texts Feb 7, 2024 · この記事では Long Prompt Weighting Stable Diffusion というものを使ってみようと思います zako-lab929. Now, you surely already know how to add brackets to put emphasis on a word (or words (or even phrase!)), but what if you want even more emphasis on that word? You could always add more brackets like ((flying)), or even ((((eating dinner with friends)))), but there is a better way! May 12, 2025 · Part II: Weight Rules and Syntax for Comfy UI Prompts Weight Expression. ComfyUI can also add the appropriate weighting syntax for a selected part of the prompt via the keybinds Ctrl + Up and Ctrl + Down. Emphasize/weigh part of your prompt with parentheses as so: a baby deer with (big eyes) De-emphasize part of your prompt as so: a [baby] deer with big eyes Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. Such weighted terms can be used to emphasize certain words or phrases in the generated image. 0 it decreases the weight Long Prompt Weighting Stable Diffusion The Pipeline lets you input prompt without 77 token length limit. A1111 for instance simply scales the associated vector by the prompt weight, while ComfyUI by default calculates a travel direction from the prompt and an empty prompt. For example, interpolating between "red hair" and "blonde hair" with continuous weights. Parameters are the things you write inside your prompts. Thus a simple way to emphasize (or de-emphasize) certain parts of the prompt is by increasing or reducing the scale of the text embedding vector that corresponds to the relevant part of the prompt. To do this, you can use the following simple syntax: Append + to a word to increase its importance, -to decrease it: Feb 13, 2023 · Using our proposed scoring method to create a weighted average prompt ensemble, our method outperforms equal average ensemble, as well as hand-crafted prompts, on ImageNet, 4 of its variants, and 11 fine-grained classification benchmarks, all while being fully automatic, optimization-free, and not requiring access to labeled validation data. ¶ How does prompt weighting work? Put the word or words you want to weight inside a parenthesis, followed by a colon and a number, like this: Beautiful woman in a rose garden, wearing a (purple lace dress:1. The easiest way to prepare the prompt-weighted embeddings is to use Compel, a text prompt Nov 7, 2023 · You probably applied prompt weighting same as A1111. Can be used to easily tweak text inputs, *e. A1111 tends to have a very weak effect of prompts compared to ComfyUI, so you must have given strong weighting to Prompt weighting works by increasing or decreasing the scale of the text embedding vector that corresponds to its concept in the prompt because you may not necessarily want the model to focus on all concepts equally. Two nodes are selectors for style and effect, each with its own weight control slider. \(1990\). Prompt weighting. Normalizes weights; Automatically adjusts relative strengths of prompts; Comparison Example. A very short example is that when Feb 5, 2024 · Prompt Weighting. How to do prompt-weighting in Diffusers Apr 20, 2023 · Contains a node that lets you set how ComfyUI should interpret up/down-weighted tokens. What do I do if I want an EXACT duplicate of the image prompt (FaceSwap option chosen) to replace the face of the person I put in Inpaint? What guidance scale, stop at, weight, all the 'forced overwrite' options, positive & negative guidance scaler sliders, ADM guidance End At Step (and what's the difference between this and the 'Stop At' under Apr 4, 2024 · Now, let’s take a closer look at the concept of stable diffusion prompt weight. Prompt weighting. How to do prompt-weighting in Diffusers I learned that prompt weighting is handled differently than Auto1111. Here is the first example compared to using the '(negative prompts: weight)' syntax (i. May 18, 2024 · Midjourney Prompting Complete Guide. vpcca sex acuet jnyu brays eniq urg lfra aity ennzd

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