You should NOT generate images with width and height that deviates too much from 512 pixels. In the second step, we use a. tl;dr : Basicaly, you are typing your FINAL target resolution, it will gives you : ; what resolution you should use according to SDXL suggestion as initial input resolution SDXL 1. Below you can see a full list of aspect ratios and resolutions represented in the training dataset: Stable Diffusion XL Resolutions. However, you can still change the aspect ratio of your images. 5 billion-parameter base model. 6B parameter model ensemble pipeline. Remember to verify the authenticity of the source to ensure the safety and reliability of the download. for 8x the pixel area. 0) stands at the forefront of this evolution. I run it following their docs and the sample validation images look great but I’m struggling to use it outside of the diffusers code. 8 (80%) High noise fraction. 9 models in ComfyUI and Vlad's SDnext. Stable Diffusion XL (SDXL) is a powerful text-to-image generation model that iterates on the previous Stable Diffusion models in three key ways: the UNet. Select base SDXL resolution, width and height are returned as INT values which can be connected to latent image inputs or other inputs such as the CLIPTextEncodeSDXL width, height,. "medium close-up of a beautiful woman in a purple dress dancing in an ancient temple, heavy rain. It's similar to how 1. The controlnet can help keep the original image. A few things I can encourage: Include in your negative prompts things like "Wet, oily skin, sunken eyes, etc. 1990s anime low resolution screengrab couple walking away in street at night. A brand-new model called SDXL is now in the training phase. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone. Enter the following activate the virtual environment: source venvinactivate. Also memory requirements—especially for model training—are disastrous for owners of older cards with less VRAM (this issue will disappear soon as better cards will resurface on second hand. Run SDXL refiners to increase the quality of output with high resolution images. 0_0. It is a much larger model. Well, its old-known (if somebody miss) about models are trained at 512x512, and going much bigger just make repeatings. "medium close-up of a beautiful woman in a purple dress dancing in an ancient temple, heavy rain. A very nice feature is defining presets. 1 so AI artists have returned to SD 1. You can go higher if your card can. Compact resolution and style selection (thx to runew0lf for hints). 0), one quickly realizes that the key to unlocking its vast potential lies in the art of crafting the perfect prompt. 9. 5 (512x512) and SD2. It is a Latent Diffusion Model that uses two fixed, pretrained text encoders ( OpenCLIP-ViT/G and CLIP-ViT/L ). The default resolution of SDXL is 1024x1024. Granted, it covers only a handful of all officially supported SDXL resolutions, but they're the ones I like the most. The memory use is great too, I can work with very large resolutions with no problem. The fine-tuning can be done with 24GB GPU memory with the batch size of 1. While you can generate at 512 x 512, the results will be low quality and have distortions. Start Training. 9 are available and subject to a research license. Compared to other leading models, SDXL shows a notable bump up in quality overall. Inpainting Workflow for ComfyUI. Then, we employ a multi-scale strategy for fine. 1 NSFW - not demonstrated Will be adopted and improved by community - that's an admission XL sucks. x and 2. Just like its predecessors, SDXL has the ability to generate image variations using image-to-image prompting, inpainting (reimagining. Or how I learned to make weird cats. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis Explained（GPTにて要約） Summary SDXL（Stable Diffusion XL）は高解像度画像合成のための潜在的拡散モデルの改良版であり、オープンソースである。モデルは効果的で、アーキテクチャに多くの変更が加えられており、データの変更だけでなく. 8M runs GitHub Paper License Demo API Examples README Train Versions (39ed52f2) Examples. The new version generates high-resolution graphics while using less processing power and requiring fewer text inputs. Back in the terminal, make sure you are in the kohya_ss directory: cd ~/ai/dreambooth/kohya_ss. This revolutionary application utilizes advanced. Low base resolution was only one of the issues SD1. This script can be used to generate images with SDXL, including LoRA, Textual Inversion and ControlNet-LLLite. In total, our dataset takes up 42GB. Stable Diffusion 2. Abstract. For comparison, Juggernaut is at 600k. We generated each image at 1216 x 896 resolution, using the base model for 20 steps, and the refiner model for 15 steps. I can regenerate the image and use latent upscaling if that’s the best way…. The AI model was trained on images of varying sizes, so you can generate results at different resolutions. fix use. To maintain optimal results and avoid excessive duplication of subjects, limit the generated image size to a maximum of 1024x1024 pixels or 640x1536 (or vice versa). . Edited: Thanks to SnooHesitations6482. SDXL offers negative_original_size, negative_crops_coords_top_left, and negative_target_size to negatively condition the model on image resolution and. This is just a simple comparison of SDXL1. If two or more buckets have the same aspect ratio, use the bucket with bigger area. In ComfyUI this can be accomplished with the output of one KSampler node (using SDXL base) leading directly into the input of another KSampler node (using. The speed hit SDXL brings is much more noticeable than the quality improvement. 5 and SDXL. The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant time, depending on your internet. DS games a resolution of 256x192. 🟠 the community gathered around the creators of Midjourney. Try to add "pixel art" at the start of the prompt, and your style and the end, for example: "pixel art, a dinosaur on a forest, landscape, ghibli style". 9vae. 1 at 1024x1024 which consumes about the same at a batch size of 4. That indicates heavy overtraining and a potential issue with the dataset. json - use resolutions-example. With 4 times more pixels, the AI has more room to play with, resulting in better composition and. "AI image generation is as good as done," CEO Mostaque said in a Q&A on the official Discord server shortly after SDXL's. Can someone for the love of whoever is most dearest to you post a simple instruction where to put the SDXL files and how to run the thing?. Le Communiqué de presse sur SDXL 1. 0 (en) de Stability (Et notre article couvrant cette annonce). SDXL v0. ; Added MRE changelog. The default value of 20 is sufficient for high quality images. Dynamic engines generally offer slightly. Tips for SDXL training. The SDXL uses Positional Encoding. On 26th July, StabilityAI released the SDXL 1. json as a template). They'll surely answer all your questions about the model :) For me, it's clear that RD's model. 5 model. 1's 860M parameters. IMO do img2img in comfyui as well. Fantasy Architecture Prompt. The training is based on image-caption pairs datasets using SDXL 1. 2000 steps is fairly low for a dataset of 400 images. 9 are available and subject to a research license. SDXL shows significant improvements in synthesized image quality, prompt adherence, and composition. It is a Latent Diffusion Model that uses two fixed, pretrained text encoders ( OpenCLIP-ViT/G and CLIP-ViT/L ). The chart above evaluates user preference for SDXL (with and without refinement) over SDXL 0. 5. Stable Diffusion XL (SDXL), is the latest AI image generation model that can generate realistic faces, legible text within the images, and better image composition, all while using shorter and simpler prompts. I cant' confirm the Pixel Art XL lora works with other ones. 9 espcially if you have an 8gb card. However, it also has limitations such as challenges in synthesizing intricate structures. Start with DPM++ 2M Karras or DPM++ 2S a Karras. 0 is highly. (As a sample, we have prepared a resolution set for SD1. You can see the exact settings we sent to the SDNext API. Here is the best way to get amazing results with the SDXL 0. bat and start to enjoy a new world of crazy resolutions without lossing speed at low resolutions. When setting resolution you have to do multiples of 64 which make it notoriously difficult to find proper 16:9 resolutions. 0 offers a variety of preset art styles ready to use in marketing, design, and image generation use cases across industries. 1536 x 640 - 12:5. SDXL for A1111 Extension - with BASE and REFINER Model support!!! This Extension is super easy to install and use. It features significant improvements and enhancements over its predecessor. ago. The AI model was trained on images of varying sizes, so you can generate results at different resolutions. 6B parameters vs SD 2. 0 is miles ahead of SDXL0. But this bleeding-edge performance comes at a cost: SDXL requires a GPU with a minimum of 6GB of VRAM,. model_id: sdxl. Negative Prompt:3d render, smooth, plastic, blurry, grainy, low-resolution, anime, deep-fried, oversaturated. SDXL's VAE is known to suffer from numerical instability issues. Some models aditionally have versions that require smaller memory footprints, which make them more suitable to be. With SDXL (and, of course, DreamShaper XL 😉) just released, I think the " swiss knife " type of model is closer then ever. If you would like to access these models for your research, please apply using one of the following links: SDXL. N'oubliez pas que la résolution doit être égale ou inférieure à 1 048 576 pixels pour maintenir la performance optimale. In addition, SDXL can generate concepts that are notoriously difficult for image models to render, such as hands and text or spatially arranged compositions (e. 0. I hope you enjoy it! MASSIVE SDXL ARTIST COMPARISON: I tried out 208 different artist names with the same subject prompt for SDXL. SDXL represents a landmark achievement in high-resolution image synthesis. SDXL 0. Compact resolution and style selection (thx to runew0lf for hints). The smallest resolution in our dataset is 1365x2048, but many images go up to resolutions as high as 4622x6753. I’ll create images at 1024 size and then will want to upscale them. SDXL was trained on a lot of 1024x1024 images so this shouldn't happen on the recommended resolutions. 5, having found the prototype your looking for then img-to-img with SDXL for its superior resolution and finish. It’s designed for professional use, and calibrated for high-resolution photorealistic images. Conclusion: Diving into the realm of Stable Diffusion XL (SDXL 1. ¡No te lo pierdas! Hoy hablaremos de SDXL, un modelo de difusión latente que ha revolucionado la calidad de imágenes generadas en alta resolución. The same goes for SD 2. We present SDXL, a latent diffusion model for text-to-image synthesis. 6B parameters vs SD1. SDXL-base-0. our model was trained with natural language capabilities! so u can prompt like you would in Midjourney or prompt like you would in regular SDXL the choice is completely up to you! ️. Skip buckets that are bigger than the image in any dimension unless bucket upscaling is enabled. SD1. (Left - SDXL Beta, Right - SDXL 0. 0. Not to throw shade, but I've noticed that while faces and hands are slightly more likely to come out correct without having to use negative prompts, in pretty much every comparison I've seen in a broad range of styles, SD 1. Unfortunately, using version 1. SDXL is a diffusion model for images and has no ability to be coherent or temporal between batches. The model is capable of generating images with complex concepts in various art styles, including photorealism, at quality levels that exceed the best image models available today. darkside1977 • 2 mo. This substantial increase in processing power enables SDXL 0. Support for custom resolutions list (loaded from resolutions. when fine-tuning SDXL at 256x256 it consumes about 57GiB of VRAM at a batch size of 4. Compared to previous versions of Stable Diffusion, SDXL leverages a three. ; Updated Comfy. 5 to inpaint faces onto a superior image from SDXL often results in a mismatch with the base image. It can handle dimensions outside this range, but doesn't do well much smaller than 768x768 in my experience. Within those channels, you can use the follow message structure to enter your prompt: /dream prompt: *enter prompt here*. There is still room for further growth compared to the improved quality in generation of hands. Then you can always upscale later (which works kind of. Detailed Explanation about SDXL sizes and where to use each size When creating images with Stable Diffusion, one important consideration is the image size or resolution. Not OP, but you can train LoRAs with kohya scripts (sdxl branch). Galactic Gemstones in native 4K with SDXL! Just playing around with SDXL again, I thought I’d see how far I can take the resolution without any upscaling and 4K seemed like the reasonable limit. Support for custom resolutions - you can just type it now in Resolution field, like "1280x640". Then again, the samples are generating at 512x512, not SDXL's minimum, and 1. . Default resolution is 1024x1024, so it's much easier to create larger images with it. compile to optimize the model for an A100 GPU. Keep in mind the default resolution for SDXL is supposed to be 1024x1024, but people are using the refiner to generate images competently at 680x680, so maybe someone should try training smaller images on the refiner instead?SDXL 1. g. 9. 9, ou SDXL 0. 0 : Un pas en avant dans la génération d'images d'IA. Set classifier free guidance (CFG) to zero after 8 steps. 0 VAE baked in has issues with the watermarking and bad chromatic aberration, crosshatching, combing. Set the resolution to 1024x1024 or one of the supported resolutions ( - 1024 x 1024, 1152 x 896, 896 x 1152, 1216 x 832, 832 x 1216, 1344 x 768, 768 x 1344, 1536 x 640, 640 x 1536. Learn how to get the best images from SDXL 1. With 3. 0 offers better design capabilities as compared to V1. Here are some examples of what I mean:Negative prompt: 3d render, smooth, plastic, blurry, grainy, low-resolution, anime. 9, trained at a base resolution of 1024 x 1024, produces massively improved image and composition detail over its predecessor. How to use the Prompts for Refine, Base, and General with the new SDXL Model. 5 so SDXL could be seen as SD 3. This looks sexy, thanks. SDXLの導入〜Refiner拡張導入のやり方をシェアします。 ①SDフォルダを丸ごとコピーし、コピー先を「SDXL」などに変更 今回の解説はすでにローカルでStable Diffusionを起動したことがある人向けです。 ローカルにStable Diffusionをインストールしたことが無い方は以下のURLが環境構築の参考になります。Stability AI launches its advanced image generation model, SDXL 0. SDXL now works best with 1024 x 1024 resolutions. 5 and 2. 14:41 Base image vs high resolution fix applied image. Max resolution. Like SD 1. Ive had some success using SDXL base as my initial image generator and then going entirely 1. 7it-1. The Stable Diffusion XL (SDXL) model is the official upgrade to the v1. Here's a simple script (also a Custom Node in ComfyUI thanks to u/CapsAdmin), to calculate and automatically set the recommended initial latent size for SDXL image generation and its Upscale Factor based on the desired Final Resolution output. By reading this article, you will learn to generate high-resolution images using the new Stable Diffusion XL 0. For example, the default value for HED is 512 and for depth 384, if I increase the value from 512 to 550, I see that the image becomes a bit more accurate. . I mean, it's also possible to use it like that, but the proper intended way to use the refiner is a two-step text-to-img. I wrote a simple script, SDXL Resolution Calculator: Simple tool for determining Recommended SDXL Initial Size and Upscale Factor for Desired Final Resolution. AI_Alt_Art_Neo_2. They will produce poor colors and image. SDXL is not trained for 512x512 resolution , so whenever I use an SDXL model on A1111 I have to manually change it to 1024x1024 (or other trained resolutions) before generating. 1024x1024 gives the best results. fit_aspect_to_bucket adjusts your aspect ratio after determining the bucketed resolution to match that resolution so that crop_w and crop_h should end up either 0 or very nearly 0. fix) workflow. 8), (something else: 1. SDXL 1. SDXL consists of a two-step pipeline for latent diffusion: First, we use a base model to generate latents of the desired output size. I installed the extension as well and didn't really notice any difference. 0 or higher. Introduction Pre-requisites Vast. Pretraining of the base model is carried out on an internal dataset, and training continues on higher resolution images, eventually incorporating multi-aspect training to handle various aspect ratios of ∼1024×1024 pixel. Static engines use the least amount of VRAM. Dynamic Engines can be configured for a range of height and width resolutions, and a range of batch sizes. I extract that aspect ratio full list from SDXL technical report below. The original Stable Diffusion model was created in a collaboration with CompVis and RunwayML and builds upon the work: High-Resolution Image Synthesis with Latent Diffusion Models. I extract that aspect ratio full list from SDXL technical report below. Comfyui is more optimized though. 9 and Stable Diffusion 1. It utilizes all the features of SDXL. yalag • 2 mo. But I also had to use --medvram (on A1111) as I was getting out of memory errors (only on SDXL, not 1. It is convenient to use these presets to switch between image sizes of SD 1. This capability allows it to craft descriptive images from simple and concise prompts and even generate words within images, setting a new benchmark for AI-generated visuals in 2023. Reply Freshionpoop. I run on an 8gb card with 16gb of ram and I see 800 seconds PLUS when doing 2k upscales with SDXL, wheras to do the same thing with 1. 1. Rank 8 is a very low LoRA rank, barely above the minimum. panchovix. DreamStudio offers a limited free trial quota, after which the account must be recharged. 0 has proclaimed itself as the ultimate image generation model following rigorous testing against competitors. The only important thing is that for optimal performance the resolution should be set to 1024x1024 or other resolutions with the same amount of pixels but a different aspect ratio. 4/5’s 512×512. I've been using sd1. Stability AI published a couple of images alongside the announcement, and the improvement can be seen between outcomes (Image Credit) arXiv. For models SDXL and custom models based on SDXL are the latest. I made a handy cheat sheet and Python script for us to calculate ratios that fit this guideline. SDXL Base model and Refiner. 0 model. You will get worse or bad results with resolutions well below 1024x1024 (I mean, in size of pixels), 768x1280 is fine for. SDXL clip encodes are more if you intend to do the whole process using SDXL specifically, they make use of. " Note the vastly better quality, much lesser color infection, more detailed backgrounds, better lighting depth. Unlike the previous SD 1. For example: 896x1152 or 1536x640 are good resolutions. Reply reply SDXL is composed of two models, a base and a refiner. 5 models. Este modelo no solo supera a las versiones. For Interfaces/Frontends ComfyUI (with various addons) and SD. SDXL is ready to turn heads. Hello, I am trying to get similar results from my local SD using sdXL_v10VAEFix model as images from online demos. resolution: 1024,1024 or 512,512 Set the max resolution to be 1024 x 1024, when training an SDXL LoRA and 512 x 512 if you are training a 1. SDXL 1. yeah, upscaling to a higher resolution will so bring out more detail with highres fix, or with img2img. orgI had a similar experience when playing with the leaked SDXL 0. Description: SDXL is a latent diffusion model for text-to-image synthesis. Steps: 30 (the last image was 50 steps because SDXL does best at 50+ steps) Sampler: DPM++ 2M SDE Karras CFG set to 7 for all, resolution set to 1152x896 for all SDXL refiner used for both SDXL images (2nd and last image) at 10 steps Realistic vision took 30 seconds on my 3060 TI and used 5gb vram SDXL took 10 minutes per image and used. Here are the image sizes that are used in DreamStudio, Stability AI’s official image generator: 21:9 – 1536 x 640; 16:9 – 1344 x 768; 3:2 – 1216 x 832; 5:4 – 1152 x 896; 1:1 – 1024 x. Stability AI a maintenant mis fin à la phase de beta test et annoncé une nouvelle version : SDXL 0. In our experiments, we found that SDXL yields good initial results without extensive hyperparameter tuning. Stable Diffusion XL, également connu sous le nom de SDXL, est un modèle de pointe pour la génération d'images par intelligence artificielle créé par Stability AI. According to the announcement blog post, "SDXL 1. Ouverture de la beta de Stable Diffusion XL. Link in comments. To prevent this from happening, SDXL accepts cropping and target resolution values that allow us to control how much (if any) cropping we want to apply to the generated images, and the level of. 0 offers a variety of preset art styles ready to use in marketing, design, and image generation use cases across industries. . With Stable Diffusion XL 1. 008/image: SDXL Fine-tuning: 500: N/A: N/A: $. Just like its predecessors, SDXL has the ability to generate image variations using image-to-image prompting, inpainting (reimagining of the selected. For example: 896x1152 or 1536x640 are good resolutions. Stability AI. SDXL Base model and Refiner. 9: The weights of SDXL-0. json - use resolutions-example. Stability AI has released the latest version of Stable Diffusion that adds image-to-image generation and other. 0 is an open-source diffusion model, the long waited upgrade to Stable Diffusion v2. August 21, 2023 · 11 min. See the help message for the usage. Compact resolution and style selection (thx to runew0lf for hints). best settings for Stable Diffusion XL 0. json as a template). Some notable improvements in the model architecture introduced by SDXL are:You don't want to train SDXL with 256x1024 and 512x512 images; those are too small. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone: The increase of model parameters is mainly due to more attention blocks and a larger cross-attention context as SDXL uses a second text encoder. This adds a fair bit of tedium to the generation session. 0 outputs. 1152 x 896 - 9:7. The default resolution of SDXL is 1024x1024. Your LoRA will be heavily influenced by the base model, so you should use one that produces the style of images that you would like to create. Model Description: This is a model that can be used to generate and modify images based on text prompts. 9. SDXL is ready to turn heads. We design multiple novel conditioning schemes and train SDXL on multiple. Docker image for Stable Diffusion WebUI with ControlNet, After Detailer, Dreambooth, Deforum and roop extensions, as well as Kohya_ss and ComfyUI. 1. this is at a mere batch size of 8. ; Updated Comfy. SDXL 1. Those extra parameters allow SDXL to generate images that more accurately adhere to complex. Part 3 - we will add an SDXL refiner for the full SDXL process. SDXL 1. impressed with SDXL's ability to scale resolution!) --- Edit - you can achieve upscaling by adding a latent upscale node after base's ksampler set to bilnear, and simply increase the noise on refiner to >0. However, there are still limitations to address, and we hope to see further improvements. SDXL 1. 0, an open model representing the next evolutionary step in text-to-image generation models. SDXL is spreading like wildfire,. 9 Model. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone: The increase of model parameters is mainly due to more attention blocks and a larger cross-attention context as SDXL uses a second text encoder. 0 emerges as the world’s best open image generation model, poised. 9 - How to use SDXL 0. VAE. It is demonstrated that SDXL shows drastically improved performance compared the previous versions of Stable Diffusion and achieves results competitive with those of black-box state-of-the-art image generators. SDXL 1. With 3. We present SDXL, a latent diffusion model for text-to-image synthesis. Of course I'm using quite optimal settings like prompt power at 4-8, generation steps between 90-130 with different samplers. Developed by Stability AI, SDXL 1. 5. This is why we also expose a CLI argument namely --pretrained_vae_model_name_or_path that lets you specify the location of a better VAE (such as this one). 9 in terms of how nicely it does complex gens involving people. The purpose of DreamShaper has always been to make "a better Stable Diffusion", a model capable of doing everything on its own, to weave dreams. 5 models for refining and upscaling. Resolution: 1024 x 1024; CFG Scale: 11; SDXL base model only image. ). 5 and 2. For frontends that don't support chaining models like this, or for faster speeds/lower VRAM usage, the SDXL base model alone can still achieve good results: The refiner has only been trained to denoise small noise levels, so. From these examples, it’s clear to see that the quality is now on par with MidJourney. requirements. target_height (actual resolution) Resolutions by Ratio: Similar to Empty Latent by Ratio, but returns integer width and height for use with other nodes. Prompt:. 0 version. 5. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Training: With 1. It. Reduce the batch size to prevent Out-of. 5 (TD-UltraReal model 512 x 512 resolution) Positive Prompts: photo, full body, 18 years old girl, punching the air, blonde hair, blue eyes, Italian, garden ,detailed face, 8k, raw, masterpiece SDXL-0. 5B parameter base model and a 6. Abstract and Figures. e. 5 model which was trained on 512×512 size images, the new SDXL 1. If the training images exceed the resolution specified here, they will be scaled down to this resolution. My resolution is 1024x1280 (which is double 512x640), and I assume I shouldn't render lower than 1024 in SDXL. 004/image: SDXL with Custom Asset (Fine-tuned) 30: 1024x1024: DDIM (and any not listed below as premium) $. It takes just under 2 minutes to render an image and starts to lag my PC when it begins decoding it. For example: 896x1152 or 1536x640 are good resolutions. sdxl-recommended-res-calc. Step 5: Recommended Settings for SDXL. r/StableDiffusion • SDXL Resolution Cheat Sheet. Higher native resolution – 1024 px compared to 512 px for v1. Stable Diffusion XL has brought significant advancements to text-to-image and generative AI images in general, outperforming or matching Midjourney in many aspects. fix applied images. 0. 1 (768x768): SDXL Resolution Cheat Sheet and SDXL Multi-Aspect Training. Fwiw, SDXL took sizes of the image into consideration (as part of conditions pass into the model), this, you should be able to use it for upscaling, downscaling, tile-based inpainting etc if the model is properly trained. Below are the presets I use. 1’s 768×768. We. . 1 is clearly worse at hands, hands down. Stable Diffusion XL (SDXL) 1. 5 Lora's are hidden. They could have provided us with more information on the model, but anyone who wants to may try it out. DSi XL has a resolution of 256x192, so obviously DS games will display 1:1. 0 model is trained on 1024×1024 dimension images which results in much better detail and quality of images generated. In those times I wasn't able of rendering over 576x576. So I won't really know how terrible it is till it's done and I can test it the way SDXL prefers to generate images. On a related note, another neat thing is how SAI trained the model. 9: The base model was trained on a variety of aspect ratios on images with resolution 1024^2. 5 is version 1. I haven't seen anything that makes the case. 0 in July 2023. That's all this node does: Select one of the officially supported resolutions and switch between horizontal and vertical aspect ratios. 9 models in ComfyUI and Vlad's SDnext. 7gb without generating anything.