In the hypernetworks folder, create another folder for you subject and name it accordingly. I just tested SDXL using --lowvram flag on my 2060 6gb VRAM and the generation time was massively improved. 5 images take 40 seconds instead of 4 seconds. -opt-sdp-no-mem-attention --upcast-sampling --no-hashing --always-batch-cond-uncond --medvram. 5 takes 10x longer. I tried comfyui, 30 sec faster on a 4 batch, but it's pain in the ass to make the workflows you need, and just what you need (IMO). This exciting development paves the way for seamless stable diffusion and Lora training in the world of AI art. Not a command line option, but an optimization implicitly enabled by using --medvram or --lowvram. add --medvram-sdxl flag that only enables --medvram for SDXL models prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . that FHD target resolution is achievable on SD 1. This is the proper command line argument to use xformers:--force-enable-xformers. I can generate at a minute (or less. Si vous avez moins de 8 Go de VRAM sur votre GPU, il est également préférable d'activer l'option --medvram pour économiser la mémoire, afin de pouvoir générer plus d'images à la fois. If I do a batch of 4, it's between 6 or 7 minutes. Things seems easier for me with automatic1111. AutoV2. 命令行参数 / 性能类. You can also try --lowvram, but the effect may be minimal. 5 and 2. 0. set COMMANDLINE_ARGS=--xformers --medvram. We invite you to share some screenshots like this from your webui here: The “time taken” will show how much time you spend on generating an image. tiffFor me I have an 8 gig vram, trying sdxl in auto1111 just tells me insufficient memory if it even loads the model and when running with --medvram image generation takes a whole lot of time, comfi ui is just better in that case for me, lower loading times, lower generation time, and get this sdxl just works and doesn't tell me my vram is shit. You can also try --lowvram, but the effect may be minimal. py in the stable-diffusion-webui folder. bat file specifically for SDXL, adding the above mentioned flag, so i don't have to modify it every time i need to use 1. 6 and the --medvram-sdxl Image size: 832x1216, upscale by 2 DPM++ 2M, DPM++ 2M SDE Heun Exponential (these are just my usuals, but I have tried others) Sampling steps: 25-30 Hires. It takes now around 1 min to generate using 20 steps and the DDIM sampler. 1024x1024 instead of 512x512), use --medvram --opt-split-attention. 6 / 4. 10. 5 because I don't need it so using both SDXL and SD1. This will save you 2-4 GB of VRAM. I have even tried using --medvram and --lowvram, not even this helps. See more posts like this in r/StableDiffusionPS medvram giving me errors and just wont go higher than 1280x1280 so i dont use it. sdxl is a completely different architecture and as such requires most extensions be revamped or refactored (with the exceptions to things that. add --medvram-sdxl flag that only enables --medvram for SDXL models prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) ( #12457 ) OnlyOneKenobiI tried some of the arguments from Automatic1111 optimization guide but i noticed that using arguments like --precision full --no-half or --precision full --no-half --medvram actually makes the speed much slower. tif, . Video Summary: In this video, we'll dive into the world of automatic1111 and the official SDXL support. --medvram or --lowvram and unloading the models (with the new option) don't solve the problem. ) -cmdflag (like --medvram-sdxl. 5GB vram and swapping refiner too , use --medvram-sdxl flag when starting r/StableDiffusion • AI Burger commercial - source @MatanCohenGrumi twitter - much better than previous monstrositiesHowever, for the good news - I was able to massively reduce this >12GB memory usage without resorting to --medvram with the following steps: Initial environment baseline. Right now SDXL 0. I installed SDXL in a separate DIR but that was super slow to generate an image, like 10 minutes. 5 because I don't need it so using both SDXL and SD1. However, I notice that --precision full only seems to increase the GPU. I have a 2060 super (8gb) and it works decently fast (15 sec for 1024x1024) on AUTOMATIC1111 using the --medvram flag. 47 it/s So a RTX 4060Ti 16GB can do up to ~12 it/s with the right parameters!! Thanks for the update! That probably makes it the best GPU price / VRAM memory ratio on the market for the rest of the year. tiff in img2img batch (#12120, #12514, #12515) postprocessing/extras: RAM savingsfinally , AUTOMATIC1111 has fixed high VRAM issue in Pre-release version 1. Recommended graphics card: MSI Gaming GeForce RTX 3060 12GB. Enter the following formula. You dont need low or medvram. 9 is still research only. To save even more VRAM set the flag --medvram or even --lowvram (this slows everything but alows you to render larger images). IXL is here to help you grow, with immersive learning, insights into progress, and targeted recommendations for next steps. 0 Everything works perfectly with all other models (1. 134 RuntimeError: mat1 and mat2 shapes cannot be multiplied (231x1024 and 768x320)It consuming like 5G vram at most time which is perfect but sometime it spikes to 5. com) and it works fine with 1. 0 repliesIt's amazing - I can get 1024x1024 SDXL images in ~40 seconds at 40 iterations euler A with base/refiner with the medvram-sdxl flag enabled now. It feels like SDXL uses your normal ram instead of your vram lol. 60 から Refiner の扱いが変更になりました。. この記事では、そんなsdxlのプレリリース版 sdxl 0. About this version. Reddit just has a vocal minority of such people. the A1111 took forever to generate an image without refiner the UI was very laggy I did remove all the extensions but nothing really change so the image always stocked on 98% I don't know why. Don't turn on full precision or medvram if you want max speed. 2 You must be logged in to vote. Reply AK_3D • Additional comment actions. add --medvram-sdxl flag that only enables --medvram for SDXL models; prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . 0. A Tensor with all NaNs was produced in the vae. So being $800 shows how much they've ramped up pricing in the 4xxx series. 1girl, solo, looking at viewer, light smile, medium breasts, purple eyes, sunglasses, upper body, eyewear on head, white shirt, (black cape:1. 35 31-666523 . 9 / 2. Reply LawProud492 • Additional comment actions. ControlNet support for Inpainting and Outpainting. I have always wanted to try SDXL, so when it was released I loaded it up and surprise, 4-6 mins each image at about 11s/it. I read the description in the sdxl-vae-fp16-fix README. 213 upvotes · 68 comments. 3: using lowvram preset is extremely slow due to. Comfy is better at automating workflow, but not at anything else. And, I didn't bother with a clean install. The advantage is that it allows batches larger than one. The disadvantage is that slows down generation of a single image SDXL 1024x1024 by a few seconds for my 3060 GPU. 5 secsIt also has a memory leak, but with --medvram I can go on and on. Not op, but using medvram makes stable diffusion really unstable in my experience, causing pretty frequent crashes. Open 1. bat file specifically for SDXL, adding the above mentioned flag, so i don't have to modify it every time i need to use 1. --medvram: None: False: Enable Stable Diffusion model optimizations for sacrificing a some performance for low VRAM usage. Funny, I've been running 892x1156 native renders in A1111 with SDXL for the last few days. VRAM使用量が少なくて済む. I switched over to ComfyUI but have always kept A1111 updated hoping for performance boosts. This model is open access and. with this --opt-sub-quad-attention --no-half --precision full --medvram --disable-nan-check --autolaunch I could have 800*600 with my 6600xt 8g, not sure if your 480 could make it. ここでは. Hey, just wanted some opinions on SDXL models. It provides an interface that simplifies the process of configuring and launching SDXL, all while optimizing VRAM usage. It takes a prompt and generates images based on that description. MASSIVE SDXL ARTIST COMPARISON: I tried out 208 different artist names with the same subject prompt for SDXL. 5 models your 12gb vram should never need the medvram setting since cost some generation speed and for very large upscaling there is several ways to upscale by use of tiles to which the 12gb is more than enough. I wanted to see the difference with those along with the refiner pipeline added. These also don't seem to cause a noticeable performance degradation, so try them out, especially if you're running into issues with CUDA running out of memory; of. Say goodbye to frustrations. It's slow, but works. I would think 3080 10gig would be significantly faster, even with --medvram. 0 - RTX2080 . Thats why i love it. bat` Beta Was this translation helpful? Give feedback. On the plus side it's fairly easy to get linux up and running and the performance difference between using rocm and onnx is night and day. I have a RTX3070 8GB and A1111 SDXL works flawless with --medvram and. . (Also why should i delete my yaml files ?)Unfortunately yes. It takes around 18-20 sec for me using Xformers and A111 with a 3070 8GB and 16 GB ram. Took 33 minutes to complete. Cannot be used with --lowvram/Sequential CPU offloading. Then things updated. My faster GPU, with less VRAM, at 0 is the Window default and continues to handle Windows video while GPU 1 is making art. Try adding --medvram to the command line argument. safetensors generation takes 9sec longer, Reply replyWith medvram Composition is usually better woth sdxl, but many finetunes are trained at higher res which reduced the advantage for me. 5, now I can just use the same one with --medvram-sdxl without having. SDXL liefert wahnsinnig gute. docker compose --profile download up --build. Web. bat file, 8GB is sadly a low end card when it comes to SDXL. 5GB vram and swapping refiner too , use --medvram-sdxl flag when starting r/StableDiffusion • SDXL 1. Note that the Dev branch is not intended for production work and may break other things that you are currently using. And, I didn't bother with a clean install. bat file at all. Zlippo • 11 days ago. I'm on Ubuntu and not Windows. Currently, only running with the --opt-sdp-attention switch. It's still around 40s to generate but that's a big difference from 40 minutes! The --no-half-vae option doesn't. For a few days life was good in my AI art world. I haven't been training much for the last few months but used to train a lot, and I don't think --lowvram or --medvram can help with training. . I get new ones : "NansException", telling me to add yet another commandline --disable-nan-check, which only helps at generating grey squares over 5 minutes of generation. 과연 얼마나 새로워졌을지. As I said, the vast majority of people do not buy xx90 series cards, or top end cards in general, for games. I have tried rolling back the video card drivers to multiple different versions. It's a small amount slower than ComfyUI, especially since it doesn't switch to the refiner model anywhere near as quick, but it's been working just fine. 0_0. I run it on a 2060, relatively easily (with -medvram). Honestly the 4070 ti is an incredibly great value card, I don't understand the initial hate it got. I don't know how this is even possible but other resolutions can get generated but their visual quality is absolutely inferior, and I'm not talking about difference in resolution. 手順2：Stable Diffusion XLのモデルをダウンロードする. TencentARC released their T2I adapters for SDXL. During renders in the official ComfyUI workflow for SDXL 0. md, and it seemed to imply that when using the SDXL model loaded on the GPU in fp16 (using . (20 steps sd xl base) PS sd 1. With SDXL every word counts, every word modifies the result. 09s/it when not exceeding my graphics card memory, 2. 0. I have used Automatic1111 before with the --medvram. Try the other one if the one you used didn’t work. bat" asなお、SDXL使用時のみVRAM消費量を抑えられる「--medvram-sdxl」というコマンドライン引数も追加されています。 通常時はmedvram使用せず、SDXL使用時のみVRAM消費量を抑えたい方は設定してみてください。 AUTOMATIC1111 ver1. 5 min. 5 images take 40. Nvidia (8GB) --medvram-sdxl --xformers; Nvidia (4GB) --lowvram --xformers; See this article for more details. This is the log: Traceback (most recent call last): File "E:stable-diffusion-webuivenvlibsite-packagesgradio outes. Details. I was using --MedVram and --no-half. The SDXL works without it. Decreases performance. If you have 4 GB VRAM and want to make images larger than 512x512 with --medvram, use --lowvram --opt-split-attention. を丁寧にご紹介するという内容になっています。. On my 3080 I have found that --medvram takes the SDXL times down to 4 minutes from 8 minutes. I am at Automatic1111 1. You can go here and look through what each command line option does. This also somtimes happens when I run dynamic prompts in SDXL and then turn them off. 🚀Announcing stable-fast v0. You have much more control. 6. Got playing with SDXL and wow! It's as good as they stay. 5 checkpoints Yeah 8gb is too little for SDXL outside of ComfyUI. While SDXL works on 1024x1024, and when you use 512x512, its different, but bad result too (like if cfg too high). 5 in about 11 seconds each. 5gb to 5. Commandline arguments: Nvidia (12gb+) --xformers Nvidia (8gb) --medvram-sdxl --xformers Nvidia (4gb) --lowvram --xformers AMD (4gb) --lowvram --opt-sub-quad-attention + TAESD in settings Both rocm and directml will generate at least 1024x1024 pictures at fp16. 8~5. add --medvram-sdxl flag that only enables --medvram for SDXL models; prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . Start your invoke. use --medvram-sdxl flag when starting. 1. Hash. 0, the various. xformers can save vram and improve performance, I would suggest always using this if it works for you. bat" asset COMMANDLINE_ARGS= --precision full --no-half --medvram --opt-split-attention (means you start SD from webui-user. then press the left arrow key to reduce it down to one. set COMMANDLINE_ARGS=--opt-split-attention --medvram --disable-nan-check --autolaunch My graphics card is 6800xt, I started with the above parameters, generated 768x512 img, Euler a, 1. AI 그림 사이트 mage. python launch. I tried comfyui, 30 sec faster on a 4 batch, but it's pain in the ass to make the workflows you need, and just what you need (IMO). 5GB vram and swapping refiner too , use --medvram-sdxl flag when starting r/StableDiffusion • [WIP] Comic Factory, a web app to generate comic panels using SDXLSeems like everyone is liking my guides, so I'll keep making them :) Today's guide is about VAE (What It Is / Comparison / How to Install), as always, here's the complete CivitAI article link: Civitai | SD Basics - VAE (What It Is / Comparison / How to. 1. 0-RC , its taking only 7. SDXL, and I'm using an RTX 4090, on a fresh install of Automatic 1111. Beta Was this translation helpful? Give feedback. In my case SD 1. The “sys” will show the VRAM of your GPU. 【Stable Diffusion】SDXL. x）. The post just asked for the speed difference between having it on vs off. --medvram VRAMが4～6GBの場合に必須です。VRAMが少なくても生成可能になりますが、若干生成速度は落ちます。. For 1 512*512 it takes me 1. I only see a comment in the changelog that you can use it but I am not. Reviewed On 7/1/2023. 6. 33 IT/S ~ 17. Consumed 4/4 GB of graphics RAM. @edgartaor Thats odd I'm always testing latest dev version and I don't have any issue on my 2070S 8GB, generation times are ~30sec for 1024x1024 Euler A 25 steps (with or without refiner in use). ComfyUIでSDXLを動かすメリット. Comparisons to 1. tiff in img2img batch (#12120, #12514, #12515) postprocessing/extras: RAM savingsSince you're not using SDXL based model, run back your . tiff in img2img batch (#12120, #12514, #12515) postprocessing/extras: RAM savings6f0abbb. py is a script for SDXL fine-tuning. 6. For a while, the download will run as follows, so wait until it is complete: 1. 5 Models. Another thing you can try is the "Tiled VAE" portion of this extension, as far as I can tell it sort of chops things up like the commandline arguments do, but without murdering your speed like --medvram does. 6,max_split_size_mb:128 git pull. Same problem. 👎 2 Daxiongmao87 and Nekos4Lyfe reacted with thumbs down emojiImage by Jim Clyde Monge. I am talking PG-13 kind of NSFW, maaaaaybe PEGI-16. I have 10gb of vram and I can confirm that it's impossible without medvram. 9 model for Automatic1111 WebUI My card Geforce GTX 1070 8gb I use A1111. 1. version: v1. Speed Optimization. not so much under Linux though. Runs faster on ComfyUI but works on Automatic1111. 1 models, you can use either. . ComfyUI allows you to specify exactly what bits you want in your pipeline, so you can actually make an overall slimmer workflow than any of the other three you've tried. I use a 2060 with 8 gig and render SDXL images in 30s at 1k x 1k. Pour Automatic1111,. 5 gets a big boost, I know there's a million of us out. S tability AI recently released its first official version of Stable Diffusion XL (SDXL) v1. api Has caused the model. Important lines for your issue. I found on the old version some times a full system reboot helped stabilize the generation. just installed and Ran ComfyUI with the following Commands: --directml --normalvram --fp16-vae --preview-method auto. I have the same issue, got an Arc A770 too so i guess the card is the problem. Last update 07-15-2023 ※SDXL 1. I've seen quite a few comments about people not being able to run stable diffusion XL 1. I've been trying to find the best settings for our servers and it seems that there are two accepted samplers that are recommended. 5 based models at 512x512 and upscaling the good ones. Say goodbye to frustrations. 2 (1Tb+2Tb), it has a NVidia RTX 3060 with only 6GB of VRAM and a Ryzen 7 6800HS CPU. SDXL can indeed generate a nude body, and the model itself doesn't stop you from fine-tuning it towards whatever spicy stuff there is with a dataset, at least by the looks of it. I have searched the existing issues and checked the recent builds/commits. Next with SDXL Model/ WindowsIf still not fixed, use command line arguments --precision full --no-half at a significant increase in VRAM usage, which may require --medvram. py, but it also supports DreamBooth dataset. 3. You should definitively try them out if you care about generation speed. 업데이트되었는데요. My hardware is Asus ROG Zephyrus G15 GA503RM with 40GB RAM DDR5. set COMMANDLINE_ARGS=--medvram --no-half-vae --opt-sdp-attention. 19--precision {full,autocast} 在这个精度下评估: evaluate at this precision: 20--shareTry setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Even with --medvram, I sometimes overrun the VRAM on 512x512 images. For most optimum result, choose 1024 * 1024 px images For most optimum result, choose 1024 * 1024 px images If still not fixed, use command line arguments --precision full --no-half at a significant increase in VRAM usage, which may require --medvram. 5 minutes with Draw Things. On Windows I must use. The suggested --medvram I removed it when i upgraded from RTX2060-6GB to RTX4080-12GB (both Laptop/Mobile). 6 and have done a few X/Y/Z plots with SDXL models and everything works well. This is the same problem. I just loaded the models into the folders alongside everything. So please don’t judge Comfy or SDXL based on any output from that. 5. 5. 5GB vram and swapping refiner too , use --medvram-sdxl flag when starting r/StableDiffusion • Year ahead - Requests for Stability AI from community?Commands Optimizations. 0). 32 GB RAM. 2gb (so not full) I tried different CUDA settings mentioned above in this thread and no change. If you have more VRAM and want to make larger images than you can usually make (e. 8~5. SDXL and Automatic 1111 hate eachother. This opens up new possibilities for generating diverse and high-quality images. India Rail Info is a Busy Junction for. Normally the SDXL models work fine using medvram option, taking around 2 it/s, but when i use Tensor RT profile for SDXL, it seems like the medvram option is not being used anymore as the iterations start taking several minutes as if the medvram option is disabled. 6. whl file to the base directory of stable-diffusion-webui. either add --medvram to your webui-user file in the command line args section (this will pretty drastically slow it down but get rid of those errors) OR. Got it updated and the weight was loaded successfully. Please use the dev branch if you would like to use it today. 9 through Python 3. safetensors at the end, for auto-detection when using the sdxl model. 5gb. 최근 스테이블 디퓨전이. Watch on Download and Install. My hardware is Asus ROG Zephyrus G15 GA503RM with 40GB RAM DDR5-4800, two M. You'd need to train a new SDXL model with far fewer parameters from scratch, but with the same shape. It defaults to 2 and that will take up a big portion of your 8GB. Just check your vram and be sure optimizations like xformers are set-up correctly because others UI like comfyUI already enable those so you don't really feel the higher vram usage of SDXL. 5x. In your stable-diffusion-webui folder, create a sub-folder called hypernetworks. amd+windows kullanıcıları es geçiliyor. At all. 5Gb free when using SDXL based model). /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. As long as you aren't running SDXL in auto1111 (which is the worst way possible to run it), 8GB is more than enough to run SDXL with a few LoRA's. 動作が速い. 2 arguments without the --medvram. (--opt-sdp-no-mem-attention --api --skip-install --no-half --medvram --disable-nan-check)RTX 4070 - have tried every variation of MEDVRAM , XFORMERS on and off and no change. I was using A1111 for the last 7 months, a 512×512 was taking me 55sec with my 1660S, SDXL+Refiner took nearly 7minutes for one picture. py file that removes the need of adding "--precision full --no-half" for NVIDIA GTX 16xx cards. 今回は Stable Diffusion 最新版、Stable Diffusion XL (SDXL)についてご紹介します。. UI. For 8GB vram, the recommended cmd flag is "--medvram-sdxl". Moved to Installation and SDXL. • 1 mo. The usage is almost the same as fine_tune. Also, don't bother with 512x512, those don't work well on SDXL. ipinz added the enhancement label on Aug 24. It will be good to have the same controlnet that works for SD1. ControlNet support for Inpainting and Outpainting. Launching Web UI with arguments: --port 7862 --medvram --xformers --no-half --no-half-vae ControlNet v1. Not a command line option, but an optimization implicitly enabled by using --medvram or --lowvram. add --medvram-sdxl flag that only enables --medvram for SDXL models prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . Disables the optimization above. 合わせ. The “sys” will show the VRAM of your GPU. With this on, if one of the images fail the rest of the pictures are. I updated to A1111 1. PLANET OF THE APES - Stable Diffusion Temporal Consistency. 5 model is that SDXL is much slower, and uses up more VRAM and RAM. 5 models are pointless, SDXL is much bigger and heavier so your 8GB card is a low-end GPU when it comes to running SDXL. . Zlippo • 11 days ago. This guide covers Installing ControlNet for SDXL model. Introducing our latest YouTube video, where we unveil the official SDXL support for Automatic1111. py bdist_wheel. set COMMANDLINE_ARGS=--xformers --medvram. They don't slow down generation by much but reduce VRAM usage significantly so you may just leave them. . 0 on 8GB VRAM? Automatic1111 & ComfyUi. 0 Version in Automatic1111 installiert und nutzen könnt. 1 until you like it. Now everything works fine with SDXL and I have two installations of Automatic1111 each working on an intel arc a770. 11. Image by Jim Clyde Monge. environ. 19it/s (after initial generation). Open 1 task done. The --medvram option addresses this issue by partitioning the VRAM into three parts, with one part allocated for the model and the other two parts for intermediate computation. 5 models your 12gb vram should never need the medvram setting since cost some generation speed and for very large upscaling there is several ways to upscale by use of tiles to which the 12gb is more than enough. . Slowed mine down on W10. @aifartist The problem was in the "--medvram-sdxl" in webui-user. 以下の記事で Refiner の使い方をご紹介しています。. T2I adapters are faster and more efficient than controlnets but might give lower quality. 10 in series: ≈ 7 seconds. Just copy the prompt, paste it into the prompt field, and click the blue arrow that I've outlined in red. ptitrainvaloin. process_api( File "E:stable-diffusion-webuivenvlibsite. there is no --highvram, if the optimizations are not used, it should run with the memory requirements the compvis repo needed. isocarboxazid increases effects of dextroamphetamine transdermal by decreasing metabolism. fix, I tried optimizing the PYTORCH_CUDA_ALLOC_CONF, but I doubt it's the optimal config for. Hash. aiイラストで一般人から一番口を出される部分が指の崩壊でしたので、そのあたりの改善の見られる sdxl は今後主力になっていくことでしょう。 今後もAIイラストを最前線で楽しむ為にも、一度導入を検討されてみてはいかがでしょうか。My GTX 1660 Super was giving black screen. You might try medvram instead of lowvram. webui-user. 0 base and refiner and two others to upscale to 2048px. There’s a difference between the reserved VRAM (around 5GB) and how much it uses when actively generating. finally , AUTOMATIC1111 has fixed high VRAM issue in Pre-release version 1. for sdxl, choose which part of prompt goes to second text encoder - just add TE2: separator in the prompt for hires and refiner, second pass prompt is used if present, otherwise primary prompt is used new option in settings -> diffusers -> sdxl pooled embeds thanks @AI-Casanova; better Hires support for SD and SDXLYou really need to use --medvram or --lowvram to just make it load on anything lower than 10GB in A1111. tif, . @echo off set PYTHON= set GIT= set VENV_DIR= set COMMANDLINE_ARGS=--medvram-sdxl --xformers call webui. --xformers --medvram. 在 WebUI 安裝同時，我們可以先下載 SDXL 的相關文件，因為文件有點大，所以可以跟前步驟同時跑。 Base模型 A user on r/StableDiffusion asks for some advice on using --precision full --no-half --medvram arguments for stable diffusion image processing.