5 right now is better than SDXL 0. Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn,. SDXL 1. This method should be preferred for training models with multiple subjects and styles. However, fine-tuning a model as large as…I created a trailer for a Lakemonster movie with MidJourney, Stable Diffusion and other AI tools. 0 release allows hi-res AI image synthesis that can run on a local machine. The default value of 20 is sufficient for high quality images. Traditional library with floor-to-ceiling bookcases, rolling ladder, large wooden desk, leather armchair, antique rug, warm lighting, high resolution textures, intellectual and inviting atmosphere ; 113: Contemporary glass and steel building with sleek lines and an innovative facade, surrounded by an urban landscape, modern, high resolution. 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. Stable Diffusion XL has brought significant advancements to text-to-image and generative AI images in general, outperforming or matching Midjourney in many aspects. Note: The base SDXL model is trained to best create images around 1024x1024 resolution. Fantasy Architecture Prompt. 0? SDXL 1. 5/SD2. Compact resolution and style selection (thx to runew0lf for hints). 0, renowned as the best open model for photorealistic image generation, offers vibrant, accurate colors, superior contrast, and detailed shadows at a native resolution of…VRAM consumption is surprisingly okay even at the resolution which is above 1024x1024 default. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. It is created by Stability AI. Output resolution is higher but at close look it has a lot of artifacts anyway. [1] Following the research-only release of SDXL 0. 0), one quickly realizes that the key to unlocking its vast potential lies in the art of crafting the perfect prompt. Then again, the samples are generating at 512x512, not SDXL's minimum, and 1. Supporting nearly 3x the parameters of Stable Diffusion v1. I'd actually like to completely get rid of the upper line (I also don't know. Plongeons dans les détails. Control Nets are compatible with SDXL, but you’ll have to download the SDXL-specific models. 9 in terms of how nicely it does complex gens involving people. SDXL is now available and so is the latest version of one of the best Stable Diffusion models. The chart above evaluates user preference for SDXL (with and without refinement) over SDXL 0. ; Added MRE changelog. 9vae. It is a more flexible and accurate way to control the image generation process. However, a game-changing solution has emerged in the form of Deep-image. 5 is Haveall, download Safetensors file and put into ComfyUImodelscheckpointsSDXL and ComfyUImodelscheckpointsSD15 )SDXL Report (official) Summary: The document discusses the advancements and limitations of the Stable Diffusion (SDXL) model for text-to-image synthesis. 5 in sd_resolution_set. Stability. The Stable Diffusion XL (SDXL) model is the official upgrade to the v1. I installed the extension as well and didn't really notice any difference. 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. I'd actually like to completely get rid of the upper line (I also don't know why I have duplicate icons), but I didn't take the time to explore it further as of now. This is a really cool feature of the model, because it could lead to people training on high resolution crispy detailed images with many smaller cropped sections. Link in comments. If you want to switch back later just replace dev with master . SDXL offers negative_original_size, negative_crops_coords_top_left, and negative_target_size to negatively condition the model on image resolution and cropping parameters. The below settings for width and height are optimal for use on SDXL 1. Height and Width: These parameters set the resolution of the image. SDXL does support resolutions for higher total pixel values, however res. SDXL is a new version of SD. Generating at 512x512 will be faster but will give you worse results. Compact resolution and style selection (thx to runew0lf for hints). 9 are available and subject to a research license. 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. " Note the vastly better quality, much lesser color infection, more detailed backgrounds, better lighting depth. With native 1024×1024 resolution, the generated images are detailed and visually stunning. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis Aside from ~3x more training parameters than previous SD models, SDXL runs on two CLIP models, including the largest OpenCLIP model trained to-date (OpenCLIP ViT-G/14), and has a far higher native resolution of 1024×1024 , in contrast to SD 1. Firstly, we perform pre-training at a resolution of 512x512. 5 and 2. The original dataset is hosted in the ControlNet repo. 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. 1, SDXL 1. Two switches, two. When setting resolution you have to do multiples of 64 which make it notoriously difficult to find proper 16:9 resolutions. If you mean you want buttons with specific resolutions/aspect ratios, you can edit aspect_ratios. For comparison, Juggernaut is at 600k. Prompt:. It. 5 to inpaint faces onto a superior image from SDXL often results in a mismatch with the base image. Use Adafactor optimizer. Support for custom resolutions - you can just type it now in Resolution field, like "1280x640". SDXL Resolution. Model Description: This is a model that can be used to generate and modify images based on text prompts. 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. 0 with some of the current available custom models on civitai. This model operates through a two-step pipeline, leveraging a base model to generate latents of the desired output size and then utilizing a specialized high-resolution model and the SDEdit technique to transform these latents based on a given. Regarding the model itself and its development: If you want to know more about the RunDiffusion XL Photo Model, I recommend joining RunDiffusion's Discord. 0 offers better design capabilities as compared to V1. 9 was yielding already. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. I highly recommend it. But what about portrait or landscape ratios? Hopefully 1024 width or height won't be the required minimum, or it would involve a lot of VRAM consumption. Most of the time it looks worse than SD2. Example SDXL 1. That way you can create and refine the image without having to constantly swap back and forth between models. It is a Latent Diffusion Model that uses two fixed, pretrained text encoders ( OpenCLIP-ViT/G and CLIP-ViT/L ). For the best results, it is recommended to generate images with Stable Diffusion XL using the following image resolutions and ratios: 1024 x 1024 (1:1 Square) 1152 x 896 (9:7) 896 x 1152 (7:9) 1216 x 832 (19:13) In this mode the SDXL base model handles the steps at the beginning (high noise), before handing over to the refining model for the final steps (low noise). Question about SDXL. A custom node for Stable Diffusion ComfyUI to enable easy selection of image resolutions for SDXL SD15 SD21. This substantial increase in processing power enables SDXL 0. SDXL consists of a two-step pipeline for latent diffusion: First, we use a base model to generate latents of the desired output size. - generally easier to use (no refiner needed, although some SDXL checkpoints state already they don't need any refinement) - will work on older GPUs. 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. Most. However, the maximum resolution of 512 x 512 pixels remains unchanged. 0 outshines its predecessors and is a frontrunner among the current state-of-the-art image generators. Just like its predecessors, SDXL has the ability to generate image variations using image-to-image prompting, inpainting (reimagining of the selected. This week Stability AI has announced the launch of its SDXL 1. The SDXL uses Positional Encoding. With SDXL (and, of course, DreamShaper XL 😉) just released, I think the " swiss knife " type of model is closer then ever. A non-overtrained model should work at CFG 7 just fine. ; Like SDXL, Hotshot-XL was trained. 1. Part 2 (this post)- we will add SDXL-specific conditioning implementation + test what impact that conditioning has on the generated images. For example: 896x1152 or 1536x640 are good resolutions. Prompt:A wolf in Yosemite National Park, chilly nature documentary film photography. Note that datasets handles dataloading within the training script. It's certainly good enough for my production work. SDXL uses base+refiner, the custom modes use no refiner since it's not specified if it's needed. SDXL 1. Yes the model is nice, and has some improvements over 1. best settings for Stable Diffusion XL 0. Stable Diffusion XL (SDXL) is one of the latest and most powerful AI image generation models, capable of creating high-resolution and photorealistic images. We generated each image at 1216 x 896 resolution, using the base model for 20 steps, and the refiner model for 15 steps. The main difference it's also censorship, most of the copyright material, celebrities, gore or partial nudity it's not generated on Dalle3. Below are the presets I use. • 4 mo. 0 base model as of yesterday. Better Tools for Animation in SD 1. Specialized Refiner Model: SDXL introduces a second SD model specialized in handling high-quality, high-resolution data; essentially, it is an img2img model that effectively captures intricate local details. " Note the vastly better quality, much lesser color infection, more detailed backgrounds, better lighting depth. Used torch. 🟠 the community gathered around the creators of Midjourney. They will produce poor colors and image. SDXL was trained on a lot of 1024x1024 images so this shouldn't happen on the recommended resolutions. Couple of notes about using SDXL with A1111. Training: With 1. Now. Enter the following activate the virtual environment: source venvinactivate. SDXL Resolution Calculator: Simple tool for determining Recommended SDXL Initial Size and Upscale Factor for Desired Final Resolution. Official list of SDXL resolutions (as defined in SDXL paper). The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. txt in the sd-webui-ar folder. It can handle dimensions outside this range, but doesn't do well much smaller than 768x768 in my experience. SDXL 1. Both I and RunDiffusion are interested in getting the best out of SDXL. ; Use gradient checkpointing. Granted, it covers only a handful of all officially supported SDXL resolutions, but they're the ones I like the most. The speed hit SDXL brings is much more noticeable than the quality improvement. Using SDXL base model text-to-image. 9 models in ComfyUI and Vlad's SDnext. Yeah, I'm staying with 1. this is at a mere batch size of 8. • 4 mo. The chart above evaluates user preference for SDXL (with and without refinement) over SDXL 0. . . 0 is particularly well-tuned for vibrant and accurate colors, with better contrast, lighting, and shadows than its predecessor, all in native 1024×1024 resolution,” the company said in its announcement. huggingface. SDXL represents a landmark achievement in high-resolution image synthesis. r/StableDiffusion • SDXL Resolution Cheat Sheet. SDXL - The Best Open Source Image Model. 0 enhancements include native 1024-pixel image generation at a variety of aspect ratios. Apu000. 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 is 3x larger and SDXL combines a second text encoder (OpenCLIP ViT-bigG/14) with the original text encoder to significantly increase the number of parameters. Recommended graphics card: ASUS GeForce RTX 3080 Ti 12GB. A well tuned SDXL model also makes it easier to further fine tune it. Stability AI is positioning it as a solid base model on which the. The point is that it didn't have to be this way. For the kind of work I do, SDXL 1. My resolution is 1024x1280 (which is double 512x640), and I assume I shouldn't render lower than 1024 in SDXL. 5 in sd_resolution_set. ; Added ability to stop image generation. Compared to other leading models, SDXL shows a notable bump up in quality overall. 1. How are people upscaling SDXL? I’m looking to upscale to 4k and probably 8k even. SDXL clip encodes are more if you intend to do the whole process using SDXL specifically, they make use of. but when it comes to upscaling and refinement, SD1. 9, and the latest SDXL 1. 9 espcially if you have an 8gb card. It is convenient to use these presets to switch between image sizes. I hope you enjoy it! MASSIVE SDXL ARTIST COMPARISON: I tried out 208 different artist names with the same subject prompt for SDXL. In addition to this, with the release of SDXL, StabilityAI have confirmed that they expect LoRA's to be the most popular way of enhancing images on top of the SDXL v1. impressed with SDXL's ability to scale resolution!) --- Edit - you can achieve upscaling by adding a latent. Abstract. Some models aditionally have versions that require smaller memory footprints, which make them more suitable to be. On 26th July, StabilityAI released the SDXL 1. 0 boasts advancements that are unparalleled in image and facial composition. 0, which is more advanced than its predecessor, 0. 0 model is trained on 1024×1024 dimension images which results in much better detail and quality of images generated. 5 users not used for 1024 resolution, and it actually IS slower in lower resolutions. 35%~ noise left of the image generation. . I still saw double and stretched bodies when going outside the 1024x1024 standard SDXL resolution. Second, If you are planning to run the SDXL refiner as well, make sure you install this extension. Stability AI has released the latest version of Stable Diffusion that adds image-to-image generation and other. Better base resolution - probably, though manageable with upscaling, and didn't help 2. Unless someone make a great finetuned porn or anime SDXL, most of us won't even bother to try SDXL Reply red286 • Additional comment actions. lighting, and shadows, all in native 1024×1024 resolution. Ive had some success using SDXL base as my initial image generator and then going entirely 1. Comparison. Source GitHub Readme. fix) 11:04 Hires. Abstract and Figures. I’ve created these images using ComfyUI. Swapped in the refiner model for the last 20% of the steps. Rank 8 is a very low LoRA rank, barely above the minimum. Results – 60,600 Images for $79 Stable diffusion XL (SDXL) benchmark results on SaladCloud This example demonstrates how to use the latent consistency distillation to distill SDXL for less timestep inference. 0, the flagship image model developed by Stability AI, stands as the pinnacle of open models for image generation. Compact resolution and style selection (thx to runew0lf for hints). Resolutions different from these may cause unintended cropping. You can see the exact settings we sent to the SDNext API. Its three times larger UNet backbone, innovative conditioning schemes, and multi-aspect training capabilities have. 🧨 DiffusersIntroduction Pre-requisites Initial Setup Preparing Your Dataset The Model Start Training Using Captions Config-Based Training Aspect Ratio / Resolution Bucketing Resume Training Batches, Epochs…Due to the current structure of ComfyUI, it is unable to distinguish between SDXL latent and SD1. 0 as the base model. 5 and the forgotten v2 models. A custom node for Stable Diffusion ComfyUI to enable easy selection of image resolutions for SDXL SD15 SD21. 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. 0 model from Stability AI is a game-changer in the world of AI art and image creation. 0, anyone can now create almost any image easily and effectively. Quick Resolution Multiplier: Takes in an integer width and height and returns width and height times the multiplier. SDXL is a cutting-edge diffusion-based text-to-image generative model designed by Stability AI. 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. just using SDXL base to run a 10 step dimm ksampler then converting to image and running it on 1. 9, trained at a base resolution of 1024 x 1024, produces massively improved image and composition detail over its predecessor. g. I’ve created these images using ComfyUI. Yes, I know SDXL is in beta, but it is already apparent. It's simply thanks to the higher native resolution so the model has more pixels to work with – if you compare pixel for. Enlarged 128x128 latent space (vs SD1. 9 Research License. 5 and 2. 9, so I guess it will do as well when SDXL 1. 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. Better prompt following, due to the use of dual CLIP encoders and some improvement in the underlying architecture that is beyond my level of understanding 😅. "AI image generation is as good as done," CEO Mostaque said in a Q&A on the official Discord server shortly after SDXL's announcement. Reduce the batch size to prevent Out-of. Therefore, it generates thumbnails by decoding them using the SD1. json file already contains a set of resolutions considered optimal for training in SDXL. The SDXL 1. SDXL 1. 1152 x 896 - 9:7. 7it-1. On a related note, another neat thing is how SAI trained the model. You should either use exactly 1024x1024 res or multiples of it. Skip buckets that are bigger than the image in any dimension unless bucket upscaling is enabled. Compact resolution and style selection (thx to runew0lf for hints). I made a handy cheat sheet and Python script for us to calculate ratios that fit this guideline. WebUIのモデルリストからSDXLを選択し、生成解像度を1024に設定、SettingsにVAEを設定していた場合はNoneに設定します。. 0. Este modelo no solo supera a las versiones. For 24GB GPU, the following options are recommended for the fine-tuning with 24GB GPU memory: Train U-Net only. 9)" Enhancing the Resolution of AI-Generated Images. May need to test if including it improves finer details. SDXL v1. Ultimate Upscale: Seamless scaling for desired details. ago. SDXL 1. You can go higher if your card can. 5/2. Le Code Source d’Automatic1111; SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis -. To try the dev branch open a terminal in your A1111 folder and type: git checkout dev. 0 is particularly well-tuned for vibrant and accurate colors, with better contrast, lighting, and shadows than its predecessor, all in native 1024×1024 resolution,” the company said in its announcement. 11:41 How many steps do Hires. 004/image: SDXL with Custom Asset (Fine-tuned) 30: 1024x1024: DDIM (and any not listed below as premium) $. SDXL offers negative_original_size, negative_crops_coords_top_left, and negative_target_size to negatively condition the model on image resolution and. However, different aspect ratios may be used effectively. 0 is released. comfy has better processing speeds and is kinder on the ram. But it appears that SDXL is just an improvement over 2. For SDXL, try to have around 1 million pixels (1024 x 1024 = 1,048,576) with both width and height divisible by 8. Much like a writer staring at a blank page or a sculptor facing a block of marble, the initial step can often be the most daunting. However, you can still change the aspect ratio of your images. SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. 5 generates good enough images at high speed. For your information, SDXL is a new pre-released latent diffusion model…SDXL model is an upgrade to the celebrated v1. Negative Prompt:3d render, smooth, plastic, blurry, grainy, low-resolution, anime, deep-fried, oversaturated. 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. People who say "all resolutions around 1024 are good" do not understand what is Positional Encoding. x have a base resolution of 512x215 and achieve best results at that resolution, but can work at other resolutions like 256x256. ). I added it as a note in my comfy workflow, and IMO it would be nice to have a list of preset resolutions in A1111. . This looks sexy, thanks. SDXL 0. Results – 60,600 Images for $79 Stable diffusion XL (SDXL) benchmark results on SaladCloudThis example demonstrates how to use the latent consistency distillation to distill SDXL for less timestep inference. for 8x the pixel area. 0 is its ability to create complex and aesthetically pleasing images with just a few words as input. The SDXL uses Positional Encoding. - loads of checkpoints, LoRAs, embeddings and extensions already released. (Left - SDXL Beta, Right - SDXL 0. Official list of SDXL resolutions (as defined in SDXL paper). 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. For 24GB GPU, the following options are recommended: Train U-Net only. 5 Lora's are hidden. Sampling sharpness is developed by Fooocus as a final solution to the problem that SDXL sometimes generates overly smooth images or images with plastic appearance. 512x256 2:1. json - use resolutions-example. 768 x 1344 - 4:7. DS games a resolution of 256x192. SDXL 0. 9)" Enhancing the Resolution of AI-Generated Images. SDXL 1. 9. Resolution: 1024 x 1024; CFG Scale: 11; SDXL base model only image. Support for custom resolutions list (loaded from resolutions. 0 is latest AI SOTA text 2 image model which gives ultra realistic images in higher resolutions of 1024. SDXL is trained with 1024x1024 images. json as a template). My full args for A1111 SDXL are --xformers --autolaunch --medvram --no-half. Not the fastest but decent. VAE. py script shows how to implement the training procedure and adapt it for Stable Diffusion XL. ¡No te lo pierdas! Hoy hablaremos de SDXL, un modelo de difusión latente que ha revolucionado la calidad de imágenes generadas en alta resolución. some stupid scripting workaround to fix the buggy implementation and to make sure it redirects you to the actual full resolution original images (which are PNGs in this case), otherwise it. 0 is highly. SDXL-base-0. 256x512 1:2. resolutions = [ # SDXL Base resolution {"width": 1024, "height": 1024}, # SDXL Resolutions, widescreen {"width": 2048, "height": 512}, {"width": 1984, "height": 512}, {"width": 1920, "height": 512}, {"width":. Author Stability. Then, we employ a multi-scale strategy for fine. ; Use Adafactor. 5 LoRA. With 3. (Left - SDXL Beta, Right - SDXL 0. ) MoonRide Edition is based on the original Fooocus. However, there are still limitations to address, and we hope to see further improvements. I have tried putting the base safetensors file in the regular models/Stable-diffusion folder. 5 LoRAs I trained on this dataset had pretty bad-looking sample images, too, but the LoRA worked decently considering my dataset is still small. Official list of SDXL resolutions (as defined in SDXL paper). View more examples . Before running the scripts, make sure to install the library's training dependencies: . 9 en détails. txt is updated to support SDXL training. mo pixels, mo problems — Stability AI releases Stable Diffusion XL, its next-gen image synthesis model New SDXL 1. They could have provided us with more information on the model, but anyone who wants to may try it out. But one style it’s particularly great in is photorealism. 6 billion, compared with 0. SD1. Official list of SDXL resolutions (as defined in SDXL paper). x and 2. If you choose to use a lower resolution, such as <code> (256, 256)</code>, the model still generates 1024x1024 images, but they'll look like the low resolution images (simpler. Added support for custom resolutions and custom resolutions list. 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). 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. 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. ago. 0 outputs. 0 ComfyUI workflow with a few changes, here's the sample json file for the workflow I was using to generate these images:. Official list of SDXL resolutions (as defined in SDXL paper). 1 latent. ; Added MRE changelog. ; Set image size to 1024×1024, or something close to 1024 for a. 5 it is. 0, allowing users to specialize the generation to specific people or products using as few as five images. Resolutions: Standard SDXL resolution 💻 How to prompt with reality check xl. Step 5: Recommended Settings for SDXL. SDXL shows significant improvements in synthesized image quality, prompt adherence, and composition. As usual, enter and negative prompt, and feel free to tweak the parameters. 0 model. IMO do img2img in comfyui as well. 5. 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. 0: Guidance, Schedulers, and. r/StableDiffusion. Here are some native SD 2. 0 offers a variety of preset art styles ready to use in marketing, design, and image generation use cases across industries. The Stability AI team takes great pride in introducing SDXL 1. I've been using sd1. Last month, Stability AI released Stable Diffusion XL 1. 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. 8M runs GitHub Paper License Demo API Examples README Train Versions (39ed52f2) Examples. Tips for SDXL training ; The default resolution of SDXL is 1024x1024. SDXL is spreading like wildfire,. 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 is 3x larger and SDXL combines a second text encoder (OpenCLIP ViT-bigG/14) with the original text encoder to significantly increase the number of parameters. 9 to create realistic imagery with greater depth and a higher resolution of 1024x1024. There is still room for further growth compared to the improved quality in generation of hands. Initiate the download: Click on the download button or link provided to start downloading the SDXL 1. Description: SDXL is a latent diffusion model for text-to-image synthesis. 5 so SDXL could be seen as SD 3. The two-model setup that SDXL uses has the base model is good at generating original images from 100% noise, and the refiner is good at adding detail at 0. Fine-tuning allows you to train SDXL on a. 1). 9 architecture. For the record I can run SDXL fine on my 3060ti 8gb card by adding those arguments. Remember to verify the authenticity of the source to ensure the safety and reliability of the download. It is mainly the resolution, i tried it, the difference was something like 1. SDXL can generate images in different styles just by picking a parameter.