Sdxl mac m2 fix I first manually installed the SDXL models (from HuggingFace) and had this problem, but then I deleted everything and installed the models from the model list in the app and now it works. Write better code with AI Code review. Skin colors do not match but face orientation is OK. The benchmark test using literally the same model gives these results. Wizard-Vicuna-13b-SUPERHOT, Mac M2 16gb unified Ram. Deforum is not supported on a Mac which is a shame. 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. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Since updating to macOS Sonoma on my M1 Pro (16GB), image generation is unusably slow (> 10 minutes for 512x512). He used 1. | Restackio Apple slices its AI image synthesis times in half with new Stable Diffusion fix. Is mac book m2 good for rendering ? Reply reply Hongthai91 Please suggest ways (except inpainting) to fix bad fingers in SDXL 1. I get the feeling SDXL is appealing to people who don't have the computational power to be a comfy-esque poweruser, were mainly There are slight discrepancies between the output of SDXL-VAE-FP16-Fix and SDXL-VAE, but the decoded images should be close enough for most purposes. Write better code with In the same way that there are workarounds to achieve high-powered gaming on a Mac, there are ways to run Stable Diffusion. Minimum Requirements. venv to create a virtual environment. Which is let´s say ok for me. When I try to upscale an image using Hires. I am on a M2 Max 32gig MacBook Pro. If it's set to Full, the VAE isn't the problem. Be the first to comment Nobody's responded to this post yet. There seems to be no interest is working on a Mac version. Ways to Install Stable Diffusion on Apple Mac Using AUTOMATIC1111: This is a more technical route that involves cloning the web UI repository, placing Stable Diffusion models in the specified directory, and running commands in the If you search the web you'll find people getting identical inference speeds on larger models on M1 max and M2 max despite the supposed GPU speed increases, because they're running up against a memory speed wall. Omg I love this SDXL - 1024x1024 - Euler a - 20 sampling steps takes 3 mins cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. I'm curious on how it manages temperature. But if I use the "crystal clear" sdxl checkpoint i dont get an all black image. This achieves an important reduction in model size, but going beyond that is tricky because model quality becomes more Describe the bug Using the instructions in the examples/text_to_image folder's readme_sdxl. Thanks, anyway. ) After testing and testing SDXL on automatic 1111 on a MAc Studio m2 here is my first result. 5, Apple M2, python 3. Here we can discuss tips, workflows, news, and how SDXL Artist Study; SDXL Art Medium; Artist Study in Midjourney; Aesthetics in Midjourney Now in the post we share how to run Stable Diffusion on a M1 or M2 Mac. (SDXL Turbo) offers a streamlined approach to image generation, particularly for users on Mac M2 systems. Adding extensions and lora adds time. 3 or higher. install -d [-v] [-g group] [-m mode] [-o owner] directory " How do I This is a test project to demonstrate how you can run SDXL Turbo on locally on mac M1/M2. It is endlessly frustrating. 10. py --disable-offload-from-vram to speed up model loading/unloading. See the model install guide if you are new to this. 10: brew install python@3. While Nvidia's RTX 3060 can generate a 512×512 image at 50 steps in approximately 8. A 1024*1024 image with SDXL base + Refiner A $1,000 PC can run SDXL faster than a $7,000 Apple M2 machine. Instant dev environments Issues SDXL training on Mac: tensor<1x77x1xf16>' and 'tensor<1xf32>' are not broadcast compatible #4266. Thankfully, u/rkiga recommended that I downgrade my Nvidia graphics drivers to version 531. it's also known for being more stable and less prone to crashing. Thanks! You signed in with another tab or window. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Welcome to the unofficial ComfyUI subreddit. Is it normal to get responses in 1-2 minutes? SVD + Hires Fix Upscale (no LCM = Better Quality Copax XL is a finetuned SDXL 1. For some reason memory bandwidth on lower end M3 models got cut down to lower than the M2 so you won't have any luck there. More posts you This video shows you how to download and install Stable Diffusion Automatic1111 and SDXL on Apple Silicone M Series Macs. The SDXL inference in Swift (PR #218) starts running but macOS crashed after a while. Controversial an app for Markdown notes and beautiful writing on Mac, iPad, iPhone, and Apple Watch. But today, I’m curious to see how much faster diffusion This video shows you how to download and install Stable Diffusion Automatic1111 and SDXL on Apple Silicone M Series Macs. Q&A. 1 (22G90) Reply reply App crashes on Mac with SDXL Unlikely. All my recent Stable Diffusion XL experiments have been on my Windows PC instead of my M2 mac, because it has a faster Nvidia 2060 GPU with more memory. => 0. x checkpoints still beat the pants off SDXL for me right now. 9vae (Some Mac M2 users may need python entry_with_update. 2 on M2 Pro I have the same issue after installed SDXL and sdxl vae extension (removing them didn't fix) it worked one time but now loading plugins like written in this ticket or running a generation task crash the whole process in the same way I ended up using a bit of help from the setup viking 1304 has done which optimizes Run Stable Diffusion XL Turbo on Mac M1/M2. fix, it actually makes the image blurry/pixelated. To krea_ai -- wanted to try this on my mac mini m2 pro with 64GB ram, just new to the SDXL game on how to get those amazing upscaling resultsSwinIR or is this the latest and best to test UltimateSDUpscale + ControlNet Tile?? As part of this release, we published two different versions of Stable Diffusion XL in Core ML. Please share your tips, tricks, and workflows for using this software to create your AI art. Old. 0 model, maybe the author of it managed to finetune it enough to make it produce enough detail without refiner. 11: What is Mixed-Bit Palettization? Last month we discussed 6-bit palettization, a post-training quantization method that converts 16-bit weights to just 6-bit per parameter. I set amphetamine to not switch off my mac and I put it to work After almost 1 hour it was at 75% of the first image (step 44/60) I haven't tried HiRes. M2 macbook air MacOS Ventura 13. Unfortunately, I find that Forge is slower doing the same renderings than Automatic1111. Specs: 3060 12GB, tried both vanilla Automatic1111 1. (Some Mac M2 users may need python entry_with_update. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a Run Stable Diffusion XL Turbo on Mac M1/M2. io on an M2 Mac Workflow Included Locked post. “High res fix” in Auto1111 speak). I think you can try 4x if you have the hardware for it. Any help is highly appreciated. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant amount of time, depending on your internet connection. In this (High RAM is necessary, because the extension has massive RAM leakages, but it's more than fast enough for my needs. The home for gaming on Mac machines! Here you will find resources, information, and a great community of Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. keep in mind, you're also using a Mac M2 and AUTOMATIC1111 has been noted to work quite well with this device. SDXL renders in under 2 minutes. Hi has anybody had any success getting Stable Diffusion to work on an M2 Mac Mini using Automatic 1111, I have got it to work on Comfyui and Draw Things, however no success when I try on Automatic 1111, is there something in the settings or scripts I need to change? SDXL_FixedVae_fp16（fix black and NAN、no watermark） I thought using 1. Table_Immediate Currently most functionality in AUTOMATIC1111's Stable Diffusion WebUI works fine on Mac M1/M2 (Apple Silicon chips). I wrote the same exact prompt I used the first time: “a cat sitting on a table” Easy as that. I hit update all and update comfy in manager, restart the browser, re-run the workflow and get the same all black image. 5 model (I set at 0. diffusers c11d11d, macOS 13. SDXL eyes fix - help . Share Add a Comment. Hiyo, thanks so much for this! I'm happy to be a tester for this. Mochi Diffusion crashes as soon as I click generate. 5 models. Run Stable Diffusion on Apple Silicon with Core ML. 16GB RAM or more. I was having very poor performance running SDXL locally in ComfyUI to the point where it was basically unusable. Do not use the high res fix section (can select none, 0 steps in the high res section), go to the refiner section instead that will be new with all your other extensions (like control net or whatever other extensions you I'm very new to this and just looking for a bit of advice. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - loloou/SimpleSDXL (Some Mac M2 users may need python entry_with_update. The lost of details from upscaling is made up later with the finetuner and refiner sampling. We'll go through all the steps below, and give you prompts to test your installation with: SDXL v1. Find and fix vulnerabilities Codespaces. @MigCurto I've got Forge running on my Mac M2 Ultra. Installation: Install Homebrew. I tried automatic1111 and ComfyUI with SDXL 1. 0_0. however, it completely depends on your requirements and what you prioritize - ease of use or performance. clone this repository. If not, change it to Full and apply the setting. No dependencies or technical knowledge needed. I removed all of that entirely and re-fetched the repo fresh following the above Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - PeterTPE/SimpleSDXL (Some Mac M2 users may need python entry_with_update. Best. 5 512x512 -> hires fix -> 768x768: ~27s SDXL 1024x1024: ~70s Reply reply Top 1% Rank by size . Hello everyone, I'm having an issue running the SDXL demo model in Automatic1111 on my M1/M2 Mac. Before running the update, I could generate an image 960x704 in ~ 1-2 minutes. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - petercncn/SimpleSDXL. I am running ComfyUI with SDXL on my MacBook Air with the M2 chip and 16GB RAM. 08 step/sec I'm wondering if you can get any reasonable generation times with an M2 Mac, lacking nVidia or true vRAM. I've not tried Textual Inversion on Mac, but DreamBooth LoRA finetuning takes about 10 minutes per 500 iterations (M2 Pro with 32GB). Been running through various SDXL models and testing. But today, I’m curious to see how much faster diffusion has gotten on a M-series mac (M2 specifically). Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - metercai/SimpleSDXL (Some Mac M2 users may need python entry_with_update. fix on SDXL . 5 based model to fix faces generated in SDXL will be a total failure. 7 seconds, the M2 takes about 23 seconds for the same task using optimized Core ML techniques. Try this: In the Settings, go to Live Previews. Write better code with AI How to install and run Stable Diffusion on Apple Silicon M1/M2 Macs - Stable Diffusion Art Stable Diffusion is a text-to-image AI that can be run on personal computers like Mac M1 or M2. It works well. You switched accounts on another tab or window. apple/coreml-stable-diffusion-xl-base is a complete pipeline, without any quantization. It also solves this error that peop On my 3080 I have found that --medvram takes the SDXL times down to 4 minutes from 8 minutes. Though the evidence seems to be against it, I'm still leaning toward a bad VAE. Right now, I generate an image with the SDXL Base + Refiner models with the following settings: MacOS: 13. Install pytorch 2. md file, I tried to train a Stable Diffusion XL model on a dataset with mixed precision, but failed becaus Planning to install Automatic 1111 or Comfy UI on MacBook M2 Pro chip. 5. Automate any workflow Codespaces. Run Stable Diffusion XL Turbo on Mac M1/M2. Please keep posted images SFW. Macos 13. - mxcl/diffusionbee 20. 0 has just been released. A Mac with M1 or M2 chip. Here are the solutions: ***Basically, install the refiner extension (sd-webui-refiner). So far it works. I'm running Automatic 1111 on a GeForce RTX 3080 Ti (12 Gb VRAM) but I have some troubles with Hires. The Best Ways to Run Stable Diffusion and SDXL on an Apple Silicon Mac The go-to image generator for AI art enthusiasts can be installed on Apple's latest hardware. Want speed like Google Colab. So SDXL is twice as fast, Yeah I have a 32GB M1 mac and a 2080 laptop, and the 2080 is already like 10 times faster than the mac, haha. My intention is to use Automatic1111 to be able to use more cutting-edge solutions that You signed in with another tab or window. 8) goes up to 17 seconds. 0. that required for stable diffusion but not available for M1/M2 Macs via brew. Open comment sort options. I find the results interesting for comparison; hopefully others will too. I was hoping for good news with SDXL. Create AI-generated art on your Mac M1, M2, M3 or M4 using The contenders are 1) Mac Mini M2 Pro 32GB Shared Memory, 19 Core GPU, 16 Core Neural Engine -vs-2) Studio M1 Max, 10 Core, with 64GB Shared RAM. ) Colab informs me I have 15GB VRAM, SDXL doesn't go above 9GB, same as 1. . Occasionally the conversion of SDXL to CoreML is completed on a Mac mini/M2 Pro/16GB ram. Manage code changes Issues Impressed with locally run SDXL Turbo results - 4 steps, 10 seconds an image in odysseyapp. 1 (22G90) Base checkpoint: sd_xl_base_1. 5 these days, and 8x batches just make it extremely powerful. 12. Oh 3200$ isn't even that expensive for a 4090! Thanks I will also look into it. I tried comfyUI and it takes about 30s to generate 768*1048 images (i have a RTX2060, 6GB vram). Mac is good for final retouch and image workflow in general, but for example in a normal pc with ryzen 5600 and rtx 3060 12 gb, the same generate only take 30 second. Who can help? @williamberman, @sayakpaul. 236 strength and 89 steps, which will take 21 Hey, i'm little bit new to SD, but i have been using Automatic 1111 to run stable diffusion. Run python -m venv . Draw Things is my SD1. Saved searches Use saved searches to filter your results more quickly Run Stable Diffusion XL Turbo on Mac M1/M2. Download the SDXL base and refiner models and put them in the models/Stable-diffusion folder as usual. Thank you! Is it fast? Or does it just use cpu? I have M2 96GB hoping I can squeeze the juice and get some fast renders. 0 on MacBook Air M2, 25 steps about 290 seconds. Controversial. SDXL is working on my Mac now. A 1024*1024 image with SDXL base + Refiner models takes just under 1 min 30 sec on a Mac Mini M2 Pro 32 GB. Question | Help Hi guys. This repository comprises: python_coreml_stable_diffusion, a Python package for converting PyTorch models to Core ML format and performing image generation with Hugging Face diffusers in Python; StableDiffusion, a Swift package that developers can add to their Xcode projects as a dependency to deploy Well, I actually used 3080 for SDXL even without medvram (I dunno it just worked), but 3090 is a beast in comparison. fix with SDXL. I tried to fix it with a complete reinstall but was not successful. Question - Help I’ve been trying out SDXL and it’s not going so well. Despite what I think are solid specs, my image generation takes several minutes per picture. 49s on M2 Ultra, almost as fast as a 3070 :) this mac studio with 76 core , 192GB memory cost around $6600 USD😟 Reply More posts you may like. But it has the negative side effect of making 1. New comments cannot be posted. If you're at inferencing/training, 48GB RTX A6000s (Ampere) are available new I rebooted it (to have a fresh start), I cleared it using Clean My Mac and I launched Fooocus again. I have an older Mac and it takes about 6-10 minutes to generate one 1024x1024 I tried automatic1111 and ComfyUI with SDXL 1. Thought I would post this in case someone has the same question and wants to know how SD performs. But High res fix is about 1:5-2 minutes. 5x upscale but I tried 2x and voila, with higher resolution, the smaller hands are fixed a lot better. 0: Are you using one of the default Fooocus checkpoints/models? If you are, get off them immediately, go to civitai, and get good ones, because those ones take way too long, and you can find way better ones in terms of suitability for your M1 Pro. 0 Please suggest negative prompts. Sort by: Best. Not sure if this will help with the issue, I also have my model How to do hires-fix properly for SDXL? Share Add a Comment. Probably after some experiments with different models and prompts it could be improved. The Base, for example, is really a challenge to force to give really photorealistic finishes for anything that isn't a The performance of the Mac M2 in running Stable Diffusion is noteworthy, especially when compared to high-end GPUs from Nvidia. Reply reply $11K - Rackmount M2 Ultra Mac Pro w/ 192GB RAM / 2TB SSD; presumably the PCIe can be used for additional storage but unlikely to be able to support extra ML GPUs The cheapest price I've seen for a new 80GB A100 is $15K, although I've seen some used ones for <$10K. Download SDXL If you are familiar with ComfyUI and have used it with Stable Diffusion models like SDXL, the fix detailed below no longer works. 5x, 2x Saved searches Use saved searches to filter your results more quickly Hey, I had the same problem yesterday with SDXL, I found a great configuration for ComfyUI for my RTX 3050 Laptop 4GB vRAM, model+refiner in 50s-55s (2nd and 3rd iteration forward). Normal Hires. 5 images take 40 seconds instead of 4 seconds. MASSIVE SDXL ARTIST COMPARISON: I tried out 208 different artist names with the same subject prompt for SDXL. Comes with a one-click installer. Right now I am using the experimental build of A1111 and it takes ~15 mins to generate a single SDXL image without refiner. macOS Monterey 12. This is a bit outdated now: "Currently, Stable Diffusion generates images fastest on high-end GPUs from Nvidia when run locally on a Windows or Linux PC. Even with the just the base model of SDXL that tends to bring back a lot of skin texture. I noticed a typo in my prompt and clicked the text box to fix it. Sorry if it was already asked but I am so confused right now so I hope more experienced of you could help me. I had no trouble upscaling it with SD 1. But the M2 Max gives me somewhere between 2-3it/s, which is faster, but doesn't really come close to the PC GPUs that there are on the market. Sep 3, 2023 Sep 29, 2023. I'm testing it now and it's promising. See what Live preview method is set to. I tried SDXL in A1111, but even after updating the UI, the images take veryyyy long time and don't finish, like they stop at 99% every time. Reload to refresh your session. Even using image sizes around 512x512 takes forever. Hi I have been using Automatic1111 with the SDXL model on a MacBook pro M2 Max 32gigs ram. I haven't tried Flux yet. 32GB ram seems to be needed. Add your thoughts and get the conversation going. SDXL-VAE-FP16-Fix SDXL-VAE-FP16-Fix is the SDXL VAE*, but modified to run in fp16 precision without generating NaNs. How to achieve similar speed on M2 Pro chip? The Mac version just isn't as optimized as the PC version. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Installing Stable Diffusion on a Mac, particularly those with Apple Silicon M1/M2 chips, offers several user-friendly options. Don't see it running on my M2 8GB Mac Mini though Can't wait to use ControlNet with it. Use --disable-nan-check commandline This TEMPORARILY will fix itself if I uninstall and reinstall, however, I have done this 4 times now, and it ALWAYS starts crashing constantly the next day. Plan and track work Code Review In the attempt to fix things, I updated to today's Pytorch nightly* and the generation speed returned approximately the same I remembered. 5 and I don’t know how to solve this. For me the best option at the moment seems to be Draw Things (free app from App Store). Run source I test with DreamShaper XL1. Which is descent. Top. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a SDXL-VAE-FP16-Fix was created by finetuning the SDXL-VAE to: keep the final output the same, but; make the internal activation values smaller, by; scaling down weights and biases within the network; There are slight discrepancies between the output of SDXL-VAE-FP16-Fix and SDXL-VAE, but the decoded images should be close enough for most purposes. After detailer/Adetailer extension in A1111 is the easiest way to fix faces/eyes as it detects and auto-inpaints them in either txt2img or img2img using unique prompt or sampler Save my name, email, and website in this browser for the next time I comment. While other models work fine, the SDXL demo model Mac Studio (M2 Ultra) CPU_AND_GPU: ORIGINAL: 20: 1. I mainly use 1. It takes up all of my memory and sometime causes memory leak as well. Contribute to mirrajabi/sdxl-turbo-mac-mps development by creating an account on GitHub. Any clue? I use Automatic1111 web UI on Google Colab Pro. Hires. I don't know why the manual install doesn't work but I'm fine now ;) Once it is done, everything in the UI becomes very sluggish. Explore stable diffusion techniques optimized for Mac M2, leveraging top open-source AI diffusion models for enhanced performance. (Remember what it was originally so you can restore it. Instant dev environments GitHub Copilot. SDXL-VAE generates NaNs in fp16 because the internal activation values are too big: SDXL-VAE-FP16-Fix was created by finetuning the SDXL-VAE to: keep the final output the same, but Macbook Air M2 with 8 GB of RAM and I updated the app before installing SDXL. ; apple/coreml-stable-diffusion-mixed-bit-palettization But honestly upscaled and processed SD1. But for a Mac, it is very fast. fix: I have tried many; latents, ESRGAN-4x, 4x-Ultrasharp, Lollypop, No matter what my configuration of 1. 9vae ComfyUI straight up runs out of memory while just loading the SDXL model on the first run. By Jose Antonio Lanz. 61 To quote them: The Installing SDXL 1. You signed out in another tab or window. Instant dev environments Copilot. Automatic1111 can produce a 512x512 image in approximately 9seconds. ComfyUI on mac m2 produces an all black image. New. Steps to Reproduce SDXL's refiner and HiResFix are just Img2Img at their core — so you can get this same result by taking the output from SDXL and running it through Img2Img with an SD v1. Instant dev environments Issues. fix or ADetailer yet as a comparison, however the SDXL Refiner provides really different types of details and results than the Base. I think his idea was to implement hires fix using the SDXL Base model. Some recent innovations have improved the performance of Stable Diffusion derived models In the attempt to fix things, I updated to today's Pytorch nightly* and the generation speed returned approximately the same I remembered. it's based on rigorous testing & refactoring, hence most users find it more reliable. maybe you can buy a Mac mini m2 for all general graphics workflow and ai, and a simple pc just for generate fast images, the rtx 3060 12 gb work super fast for ai. Well, it takes about 35~50 seconds for whatever I type to show up in the UI. Thanks Share Add a Comment. The same with Refiner (0. I'm looking for help with some Upscaler issues i have on my M1Pro Mac Studio 32GB Ram, using the automatic1111 build from github. If I run a 1024x1024 image (DPM++2M SDE Karras - 25 Steps), I get the final image in 12 seconds. If you remove those same models does everything work again? I have this working on my macs (even a pitiful mac mini M1) and older PC and everything has been working. It also solves this error that peop All my recent Stable Diffusion XL experiments have been on my Windows PC instead of my M2 mac, because it has a faster Nvidia 2060 GPU with more memory. I'm trying to get this setup on an M1 Max laptop; I removed a previous version that I'd installed with the "old" instructions (which didn't actually work; I had to do some file editing per this thread, which finally yielded a functional UI session). 0 models on Windows or Mac. Install Python 3. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - grady-lee/SimpleSDXL. It's a massive quality improvement over previous models, however runs quite slowly on Macs. Find and fix vulnerabilities Actions. 9vae Refiner checkpoint: sd_xl_refiner_1. fix with SDXL is broken. gqvu cmmool zokdm iqgbm loqocbtp dou dfm vcy jobdk ueoklg