Refiner. 3 seconds for 30 inference steps, a benchmark achieved by. L’interface de configuration du Refiner apparait. text_l & refiner: "(pale skin:1. wait for it to load, takes a bit. If you have the SDXL 1. io in browser. SDXL is just another model. It means max. Stable Diffusion XL or SDXL is the latest image generation model that is tailored towards more photorealistic outputs with more detailed imagery and composition compared to previous SD models, including SD 2. xのcheckpointを入れているフォルダに. 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. However, I've found that adding the refiner step usually means that the refiner doesn't understand the subject, which often makes using the refiner worse with subject generation. 0 vs SDXL 1. Updating ControlNet. 1:06 How to install SDXL Automatic1111 Web UI with my automatic installer . 25:01 How to install and use ComfyUI on a free Google Colab. md. With SDXL you can use a separate refiner model to add finer detail to your output. r/StableDiffusion. All images were generated at 1024*1024. 0. 次にSDXLのモデルとVAEをダウンロードします。 SDXLのモデルは2種類あり、基本のbaseモデルと、画質を向上させるrefinerモデルです。 どちらも単体で画像は生成できますが、基本はbaseモデルで生成した画像をrefinerモデルで仕上げるという流れが一般的なよう. With the refiner they're noticeable better but it takes a very long time to generate the image (up to five minutes each). Stability AI は、他のさまざまなモデルと比較テストした結果、SDXL 1. Overall all I can see is downsides to their openclip model being included at all. . SDXL. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. Always use the latest version of the workflow json file with the latest version of the. . It is a much larger model. My current workflow involves creating a base picture with the 1. The Base and Refiner Model are used sepera. This feature allows users to generate high-quality images at a faster rate. 1. You can use a refiner to add fine detail to images. Even adding prompts like goosebumps, textured skin, blemishes, dry skin, skin fuzz, detailed skin texture, blah. A properly trained refiner for DS would be amazing. os, gpu, backend (you can see all. Having it enabled the model never loaded, or rather took what feels even longer than with it disabled, disabling it made the model load but still took ages. . A switch to choose between the SDXL Base+Refiner models and the ReVision model A switch to activate or bypass the Detailer, the Upscaler, or both A (simple) visual prompt builder To configure it, start from the orange section called Control Panel. 3. 0 where hopefully it will be more optimized. 0 it never switches and only generates with base model. 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. SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model is used to generate (noisy) latents, which are then further processed with. Reply reply litekite_SDXL Examples . 0 outshines its predecessors and is a frontrunner among the current state-of-the-art image generators. The SDXL refiner is incompatible and you will have reduced quality output if you try to use the base model refiner with DynaVision XL. What does it do, how does it work? Thx. 0_0. I was surprised by how nicely the SDXL Refiner can work even with Dreamshaper as long as you keep the steps really low. The LORA is performing just as good as the SDXL model that was trained. this applies to both sd15 and sdxl thanks @AI-Casanova for porting compel/sdxl code; mix&match base and refiner models (experimental): most of those are "because why not" and can result in corrupt images, but some are actually useful also note that if you're not using actual refiner model, you need to bump refiner stepsI 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. Based on a local experiment, full inference with both the base and refiner model requires about 11301MiB VRAM. It is too big to display, but you can still download it. But these improvements do come at a cost; SDXL 1. Txt2Img or Img2Img. 5 models. 1024 - single image 20 base steps + 5 refiner steps - everything is better except the lapels Image metadata is saved, but I'm running Vlad's SDNext. I wanted to document the steps required to run your own model and share some tips to ensure that you are starting on the right foot. SDXL works "fine" with just the base model, taking around 2m30s to create a 1024x1024 image (SD1. The chart above evaluates user preference for SDXL (with and without refinement) over Stable Diffusion 1. The model itself works fine once loaded, haven't tried the refiner due to the same RAM hungry issue. SDXL は従来のモデルとの互換性がないのの、高いクオリティの画像生成能力を持って. After the first time you run Fooocus, a config file will be generated at Fooocusconfig. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. With Tiled Vae (im using the one that comes with multidiffusion-upscaler extension) on, you should be able to generate 1920x1080, with Base model, both in txt2img and img2img. 5. You know what to do. I will focus on SD. to join this conversation on GitHub. 0, which comes with 2 models and a 2-step process: the base model is used to generate noisy latents, which are processed with a refiner model specialized for denoising (practically, it makes the. sd_xl_refiner_1. . To use the refiner model: Navigate to the image-to-image tab within AUTOMATIC1111 or. This is well suited for SDXL v1. In my PC, yes ComfyUI + SDXL also doesn't play well with 16GB of system RAM, especialy when crank it to produce more than 1024x1024 in one run. 5. Is the best balanced I could find between image size (1024x720), models, steps (10+5 refiner), samplers/schedulers, so we can use SDXL on our laptops without those expensive/bulky desktop GPUs. 0. 9. 1:39 How to download SDXL model files (base and refiner) 2:25 What are the upcoming new features of Automatic1111 Web UI. darkside1977 • 2 mo. To begin, you need to build the engine for the base model. If this interpretation is correct, I'd expect ControlNet. Download the first image then drag-and-drop it on your ConfyUI web interface. Scheduler of the refiner has a big impact on the final result. safetensors. 5 + SDXL Base+Refiner - using SDXL Base with Refiner as composition generation and SD 1. 0 introduces denoising_start and denoising_end options, giving you more control over the denoising process for fine. Read here for a list of tips for optimizing inference: Optimum-SDXL-Usage. SDXL is only for big buffy GPU's, so good luck with that, and. Reporting my findings: Refiner "disables" loras also in sd. I've been using the scripts here to fine tune the base SDXL model for subject driven generation to good effect. Installing ControlNet for Stable Diffusion XL on Google Colab. One is the base version, and the other is the refiner. 4/1. 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. SDXL includes a refiner model specialized in denoising low-noise stage images to generate higher-quality images from the base model. 5以降であればSD1. 0: Guidance, Schedulers, and Steps SDXL-refiner-0. SDXLのRefinerモデルに対応し、その他UIや新しいサンプラーなど以前のバージョンと大きく変化しています。 この記事では、ver1. sdf output-dir/. InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. Download the first image then drag-and-drop it on your ConfyUI web interface. In today’s development update of Stable Diffusion WebUI, now includes merged support for SDXL refiner. 1. This ability emerged during the training phase of the AI, and was not programmed by people. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. 0 mixture-of-experts pipeline includes both a base model and a refinement model. The Refiner checkpoint serves as a follow-up to the base checkpoint in the image quality improvement process. This is using the 1. 0 vs SDXL 1. 1) increases the emphasis of the keyword by 10%). The refiner is a new model released with SDXL, it was trained differently and is especially good at adding detail to your images. 0 Refiner model. Template Features. 5. The SDXL 1. In this video we'll cover best settings for SDXL 0. By reading this article, you will learn to do Dreambooth fine-tuning of Stable Diffusion XL 0. First image is with base model and second is after img2img with refiner model. 6 billion, compared with 0. Stability is proud to announce the release of SDXL 1. SDXL is trained with 1024*1024 = 1048576 sized images with multiple aspect ratio images , so your input size should not greater than that number. and the refiner basically destroys it (and using the base lora breaks), so I assume yes. Overall, SDXL 1. 0 / sd_xl_refiner_1. Select None in the Stable. Stable Diffusion XL. add weights. VRAM settings. Img2Img batch. Without the refiner enabled the images are ok and generate quickly. keep the final output the same, but. next (vlad) and automatic1111 (both fresh installs just for sdxl). -Img2Img SDXL Mod - In this workflow SDXL refiner works as a standard img2img model. I tried comfyUI and it takes about 30s to generate 768*1048 images (i have a RTX2060, 6GB vram). This tutorial is based on the diffusers package, which does not support image-caption datasets for. AUTOMATIC1111 版 WebUI は、Refiner に対応していませんでしたが、Ver. Part 4 - we intend to add Controlnets, upscaling, LORAs, and other custom additions. But, as I ventured further and tried adding the SDXL refiner into the mix, things. Originally Posted to Hugging Face and shared here with permission from Stability AI. 0 base model. 5 and 2. Installing ControlNet. add weights. juggXL + refiner 2 steps: In this case, there is a base SDXL model and an optional "refiner" model that can run after the initial generation to make images look better. 0 が正式リリースされました この記事では、SDXL とは何か、何ができるのか、使ったほうがいいのか、そもそも使えるのかとかそういうアレを説明したりしなかったりします 正式リリース前の SDXL 0. The total number of parameters of the SDXL model is 6. SDXL使用環境構築について SDXLは一番人気のAUTOMATIC1111でもv1. This file can be edited for changing the model path or default. 0 refiner works good in Automatic1111 as img2img model. CFG Scale and TSNR correction (tuned for SDXL) when CFG is bigger. x models through the SDXL refiner, for whatever that's worth! Use Loras, TIs, etc, in the style of SDXL, and see what more you can do. But imho training the base model is already way more efficient/better than training SD1. with sdxl . StabilityAI has created a completely new VAE for the SDXL models. This method should be preferred for training models with multiple subjects and styles. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. a closeup photograph of a. Using SDXL 1. Note: to control the strength of the refiner, control the "Denoise Start" satisfactory results were between 0. I'm using Comfy because my preferred A1111 crashes when it tries to load SDXL. Join. g. 5 + SDXL Base - using SDXL as composition generation and SD 1. Set denoising strength to 0. 5 comfy JSON and import it sd_1-5_to_sdxl_1-0. 23:06 How to see ComfyUI is processing the which part of the workflow. 0, with additional memory optimizations and built-in sequenced refiner inference added in version 1. Automate any workflow Packages. Searge-SDXL: EVOLVED v4. 5 (TD-UltraReal model 512 x 512 resolution) Positive Prompts: side profile, imogen poots, cursed paladin armor, gloomhaven, luminescent, haunted green swirling souls, evil inky swirly ripples, sickly green colors, by greg manchess, huang guangjian, gil elvgren, sachin teng, greg rutkowski, jesper ejsing, ilya. But then, I use the extension I've mentionned in my first post and it's working great. safetensors:The complete SDXL models are expected to be released in mid July 2023. I've successfully downloaded the 2 main files. Available at HF and Civitai. Judging from other reports, RTX 3xxx are significantly better at SDXL regardless of their VRAM. 0 involves an impressive 3. SDXL Base (v1. No virus. 5 based counterparts. 0 where hopefully it will be more optimized. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. 0) SDXL Refiner (v1. added 1. That being said, for SDXL 1. I will first try out the newest sd. 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. Base sdxl mixes openai clip and openclip, while the refiner is openclip only. But, as I ventured further and tried adding the SDXL refiner into the mix, things took a turn for the worse. SDXL-REFINER-IMG2IMG This model card focuses on the model associated with the SD-XL 0. It fine-tunes the details, adding a layer of precision and sharpness to the visuals. 5x), but I can't get the refiner to work. Set percent of refiner steps from total sampling steps. These images can then be further refined using the SDXL Refiner, resulting in stunning, high-quality AI artwork. 0 model) the images came out all weird. Thanks for the tips on Comfy! I'm enjoying it a lot so far. 5 upscaled with Juggernaut Aftermath (but you can of course also use the XL Refiner) If you like the model and want to see its further development, feel free to write it in the comments. json. Next, select the base model for the Stable Diffusion checkpoint and the Unet profile for. 23-0. I recommend using the DPM++ SDE GPU or the DPM++ 2M SDE GPU sampler with a Karras or Exponential scheduler. 1. Got playing with SDXL and wow! It's as good as they stay. SDXL consists of a two-step pipeline for latent diffusion: First, we use a base model to generate latents of the desired output size. And + HF Spaces for you try it for free and unlimited. SDXL apect ratio selection. 1: The standard workflows that have been shared for SDXL are not really great when it comes to NSFW Lora's. 🧨 DiffusersSDXL vs DreamshaperXL Alpha, +/- Refiner. The SDXL 1. Screenshot: # SDXL Style Selector SDXL uses natural language for its prompts, and sometimes it may be hard to depend on a single keyword to get the correct style. -Img2Img SDXL Mod - In this workflow SDXL refiner works as a standard img2img model. Support for SD-XL was added in version 1. 0 Refiner Model; Samplers. Instead you have to let it VAEdecode to an image, then VAEencode it back to a latent image with the VAE from SDXL and then upscale. The sample prompt as a test shows a really great result. I created this comfyUI workflow to use the new SDXL Refiner with old models: Basically it just creates a 512x512 as usual, then upscales it, then feeds it to the refiner. Also for those wondering, the refiner can make a decent improvement in quality with third party models (including juggXL), esp. 5とsdxlの大きな違いはサイズです。use the base model to produce an image, and subsequently use the refiner model to add more details to the image (this is how SDXL was originally trained) Base + refiner model. The model itself works fine once loaded, haven't tried the refiner due to the same RAM hungry issue. " GitHub is where people build software. I don't want it to get to the point where people are just making models that are designed around looking good at displaying faces. Try reducing the number of steps for the refiner. 0 Base Only 多出4%左右 Comfyui工作流：Base onlyBase + RefinerBase + lora + Refiner SD1. stable-diffusion-xl-refiner-1. Thanks, it's interesting to look mess with!The SDXL Base 1. 5d4cfe8 about 1 month. Click on the download icon and it’ll download the models. 5 to SDXL cause the latent spaces are different. Not OP, but you can train LoRAs with kohya scripts (sdxl branch). 90b043f 4 months ago. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1. 3. Stable Diffusion XL comes with a Base model / checkpoint plus a Refiner. The refiner model works, as the name suggests, a method of refining your images for better quality. Contribute to camenduru/sdxl-colab development by creating an account on GitHub. 0モデル SDv2の次に公開されたモデル形式で、1. Restart ComfyUI. Update README. Part 3 (this post) - we will add an SDXL refiner for the full SDXL process. Not sure if adetailer works with SDXL yet (I assume it will at some point), but that package is a great way to automate fixing. The implentation is done as described by Stability AI as an ensemble of experts pipeline for latent diffusion: In a first step, the base model is. . and have to close terminal and restart a1111 again. In the second step, we use a specialized high-resolution model and apply a technique called SDEdit (also known as "img2img") to the latents genera…Use in Diffusers. 0 is a testament to the power of machine learning, capable of fine-tuning images to near perfection. Part 3 ( link ) - we added the refiner for the full SDXL process. Yesterday, I came across a very interesting workflow that uses the SDXL base model, any SD 1. HOWEVER, surprisingly, GPU VRAM of 6GB to 8GB is enough to run SDXL on ComfyUI. With Automatic1111 and SD Next i only got errors, even with -lowvram. 2 (1Tb+2Tb), it has a NVidia RTX 3060 with only 6GB of VRAM and a Ryzen 7 6800HS CPU. Generating images with SDXL is now simpler and quicker, thanks to the SDXL refiner extension!In this video, we are walking through the installation and use o. Learn how to use the SDXL model, a large and improved AI image model that can generate realistic people, legible text, and diverse art styles. For both models, you’ll find the download link in the ‘Files and Versions’ tab. Customization. safetensors refiner will not work in Automatic1111. 0 Refiner Extension for Automatic1111 Now Available! So my last video didn't age well hahaha! But that's ok! Now that there is an exten. 0 model and its Refiner model are not just any ordinary tech models. 90b043f 4 months ago. Reload ComfyUI. Install sd-webui-cloud-inference. Per the announcement, SDXL 1. In my understanding, the base model should take care of ~75% of the steps, while the refiner model should take over the remaining ~25%, acting a bit like an img2img process. 0 as the base model. Also SDXL was trained on 1024x1024 images whereas SD1. Le modèle de base établit la composition globale. 9 + Refiner - How to use Stable Diffusion XL 0. Two models are available. This uses more steps, has less coherence, and also skips several important factors in-between I recommend you do not. If you would like to access these models for your research, please apply using one of the following links: SDXL-base-0. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. Suddenly, the results weren't as natural, and the generated people looked a bit too. 皆様ご機嫌いかがですか、新宮ラリです。 本日は、SDXL用アニメ特化モデルを御紹介します。 二次絵アーティストさんは必見です😤 Animagine XLは高解像度モデルです。 優れた品質のアニメスタイルの厳選されたデータセット上で、バッチサイズ16で27000のグローバルステップを経て、4e-7の学習率. 3. SDXL 1. 0 Base and Refiners models downloaded and saved in the right place, it should work out of the box. Base SDXL model will stop at around 80% of completion (Use TOTAL STEPS and BASE STEPS to control how much noise will go to refiner), left some noise and send it to Refine SDXL Model for completion - this is the way of SDXL. 0 / sd_xl_refiner_1. 0 Base model used in conjunction with the SDXL 1. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. I also need your help with feedback, please please please post your images and your. batch size on Txt2Img and Img2Img. 0 Base and Refiner models An automatic calculation of the steps required for both the Base and the Refiner models A quick selector for the right image width/height combinations based on the SDXL training set An XY Plot function ControlNet pre-processors, including the new XL OpenPose (released by Thibaud Zamora)SDXL on Vlad Diffusion. . You can disable this in Notebook settingsSD1. 3:08 How to manually install SDXL and Automatic1111 Web UI. With SDXL I often have most accurate results with ancestral samplers. download history blame contribute. You want to use Stable Diffusion, use image generative AI models for free, but you can't pay online services or you don't have a strong computer. json: sdxl_v0. 5 보다 훨씬 좋아진SDXL을 사용할 수 있게 되었는데훨씬 높아진 퀄리티는 기본에어느 정도의 텍스트 입력도 지원하고그림의 디테일을 보완할 때 사용하는 Refiner도 추가되었다WebUI 에서도 이제 SDXL을 지원하여아래 내용을. @bmc-synth You can use base and/or refiner to further process any kind of image, if you go through img2img (out of latent space) and proper denoising control. Please tell me I don't have to design my own. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance. 9 模型啦 快来康康吧!，第三期 最新最全秋叶大佬1. SDXL Base model and Refiner. The model is released as open-source software. This one feels like it starts to have problems before the effect can. Based on my experience with People-LoRAs, using the 1. 0は、Stability AIのフラッグシップ画像モデルであり、画像生成のための最高のオープンモデルです。. SDXL has an optional refiner model that can take the output of the base model and modify details to improve accuracy around things like hands and faces that often get messed up. I've found that the refiner tends to. 0 base. Evaluation. The SDXL base checkpoint can be used like any regular checkpoint in ComfyUI. NEXT、ComfyUIといったクライアントに比較してできることは限られ. The refiner model in SDXL 1. leepenkman • 2 mo. 5 and 2. 0 👑. In the AI world, we can expect it to be better. Anything else is just optimization for a better performance. 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. im just re-using the one from sdxl 0. I wanted to share my configuration for ComfyUI, since many of us are using our laptops most of the time. next models\Stable-Diffusion folder. . I did extensive testing and found that at 13/7, the base does the heavy lifting on the low-frequency information, and the refiner handles the high-frequency information, and neither of them interferes with the other's specialtyIve had some success using SDXL base as my initial image generator and then going entirely 1. Part 2 ( link )- we added SDXL-specific conditioning implementation + tested the impact of conditioning parameters on the generated images. Second picture is base SDXL, then SDXL + Refiner 5 Steps, then 10 Steps and 20 Steps. An SDXL base model in the upper Load Checkpoint node. If you only have a LoRA for the base model you may actually want to skip the refiner or at least use it for fewer steps. Ensemble of. 0 Base Model; SDXL 1. go to img2img, choose batch, dropdown refiner, use the folder in 1 as input and the folder in 2 as output. You. Here's what I've found: When I pair the SDXL base with my LoRA on ComfyUI, things seem to click and work pretty well. stable-diffusion-xl-refiner-1. For you information, DreamBooth is a method to personalize text-to-image models with just a few images of a subject (around 3–5). But these improvements do come at a cost; SDXL 1. I also need your help with feedback, please please please post your images and your. Définissez à partir de quel moment le Refiner va intervenir. The model is trained for 40k steps at resolution 1024x1024 and 5% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. Sorry this took so long, when putting the VAE and Model files manually in the proper modelssdxl and modelssdxl-refiner folders: Traceback (most recent call last): File "D:aiinvoke-ai-3. Open omniinfer. Part 2 ( link )- we added SDXL-specific conditioning implementation + tested the impact of conditioning parameters on the generated images. The style selector inserts styles to the prompt upon generation, and allows you to switch styles on the fly even thought your text prompt only describe the scene. Part 4 - this may or may not happen, but we intend to add upscaling, LORAs, and other custom additions. 0-refiner Model Card Model SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model (available here: is used to generate (noisy) latents, which are then further processed with a refinement model specialized for the final. the new version should fix this issue, no need to download this huge models all over again. The other difference is 3xxx series vs. Enlarge / Stable Diffusion XL includes two text. SDXL is just another model. sdxl is a 2 step model. refiner is an img2img model so you've to use it there. x during sample execution, and reporting appropriate errors. We will see a FLOOD of finetuned models on civitai like "DeliberateXL" and "RealisiticVisionXL" and they SHOULD be superior to their 1. 16:30 Where you can find shorts of ComfyUI. makes them available for SDXL always show extra networks tabs in the UI use less RAM when creating models (#11958, #12599) textual inversion inference support for SDXL extra networks. 1 to 0. 🚀 I suggest you to use: 1024x1024, 1024x1368So as long as the model is loaded in the checkpoint input and you're using a resolution of at least 1024 x 1024 (or the other ones recommended for SDXL), you're already generating SDXL images. Download both from CivitAI and move them to your ComfyUI/Models/Checkpoints folder. 08 GB. To use the refiner model: Navigate to the image-to-image tab within AUTOMATIC1111 or. 5 model. But you need to encode the prompts for the refiner with the refiner CLIP. Last, I also performed the same test with a resize by scale of 2: SDXL vs SDXL Refiner - 2x Img2Img Denoising Plot. 5, so currently I don't feel the need to train a refiner. Click “Manager” in comfyUI, then ‘Install missing custom nodes’. 9 working right now (experimental) Currently, it is WORKING in SD. For today's tutorial I will be using Stable Diffusion XL (SDXL) with the 0. It's trained on multiple famous artists from the anime sphere (so no stuff from Greg. 🧨 Diffusers Refiner は、SDXLで導入された画像の高画質化の技術で、2つのモデル Base と Refiner の 2パスで画像を生成することで、より綺麗な画像を生成するようになりました。. The workflow should generate images first with the base and then pass them to the refiner for further. Just to show a small sample on how powerful this is. 2. Refine image quality. x, SD2. 3-0. The SDXL refiner is incompatible and you will have reduced quality output if you try to use the base model refiner with NightVision XL. If the problem still persists I will do the refiner-retraining. SDXL most definitely doesn't work with the old control net. 5B parameter base model and a 6. ago. Rendered using various steps and CFG values, Euler a for the sampler, no manual VAE override (default VAE), and no refiner model. py ", line 671, in lifespanwhen ckpt select sdxl it has a option to select refiner model and works as refiner 👍 13 bjornlarssen, toyxyz, le-khang, daxijiu, djdookie, bdawg, alexclerick, zatt, Kadah, oliverban, and 3 more reacted with thumbs up emoji 🚀. The training is based on image-caption pairs datasets using SDXL 1. stable-diffusion-xl-refiner-1. Update README. 9 with updated checkpoints, nothing fancy, no upscales, just straight refining from latent. 5. image padding on Img2Img. Notebook instance type: ml. nightly Info - Token - Model.