ckpt) from the Stable Diffusion repository on Hugging Face. 1 en local sur un Mac avec processeur M1. This is one of the most powerful and cost-effective machines available on the Lightning Platform. First, you need to install a Python distribution that supports arm64 (Apple Silicon) architecture. Arguably more impressively, even an M1 iPad Pro can do the job in under 30 seconds. But while getting Stable Diffusion working on Linux and Windows is a breeze, getting it working on macOS appears to be a lot more difficult — at least based the experiences of others. Note: Ensure you run Some popular official Stable Diffusion models are: Stable DIffusion 1. " Dec 1, 2022 · Next Steps. Stable Diffusion web UI もおすすめです。 It costs like 7k$. I used Automatic1111's WebUI Stable Diffusion with a lot of models. Feb 27, 2023 · Windows, MacOS, or Linux operating system. Some popular official Stable Diffusion models are: Stable DIffusion 1. 😳 In the meantime, there are other ways to play around with Stable Diffusion. さっそく動かしてみたいなと思って触ってみることにしましたが、手元にあるのはMacBook Sep 5, 2022 · cd stable-diffusion mkdir -p models/ldm/stable-diffusion-v1/ Step Three: Set up a Virtualenv to Install the Dependencies. 自動で開かない場合は、SafariやChromeのアドレス We would like to show you a description here but the site won’t allow us. 0 ( 768-v-ema Apple needs to up their AI game 😀 I used diffusion be on M1 but gave up and bought a nvidia 3060 for more speed and API plug-in to Photoshop. Fully supports SD1. 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 Dec 2, 2022 · Currently, Stable Diffusion generates images fastest on high-end GPUs from Nvidia when run locally on a Windows or Linux PC. 19. Well, since late 2022, AI generated Art becomes sensational and revolutionary as you can create high quality of images and paints with some prompts. Apr 10, 2023 · MacbookでStable Diffusionを試した記事です。. Oct 23, 2023 · I am benchmarking these 3 devices: macbook Air M1, macbook Air M2 and macbook Pro M2 using ml-stable-diffusion. A graphics card with at least 4GB of VRAM. Its installation process is no different from any other app. Pour profiter d'une vitesse raisonnable, assurez-vous d'utiliser un Mac équipé d'une puce Apple Silicon (M1, M2 ou M3) et, idéalement, de 16 Go de mémoire ou plus. 12GB or more install space. My intention is to use Automatic1111 to be able to use more cutting-edge solutions that (the excellent) DrawThings allows. Python 3. The model file for Stable Diffusion is hosted on Hugging Face. Sep 6, 2022 · Stable Diffusion is an open machine learning model developed by Stability AI to generate digital images from natural language descriptions that has become really popular in the last weeks. 最後還會介紹如何下載 Stable Diffusion 模型，並提供一些熱門模型的下載連結。. Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything. Note: Stable Diffusion v1 is a general text-to-image diffusion Yeah I run a 6800XT with latest ROCm and Torch and get performance at least around a 3080 for Automatic's stable diffusion setup. For example, an M1 Air with 16GB of RAM will run it. Dec 26, 2023 · I ran this code on my M1 Mac (32GB, 8 core [6 performance, 2 efficiency]). 結論から言って、M1は比較的実用的な画像を18から21秒で一枚生成できました。. 3. x, SDXL, Stable Video Diffusion and Stable Cascade; Asynchronous Queue system; Many optimizations: Only re-executes the parts of the workflow that changes between executions. I'm seeing much faster image output on that compared to my beastly M1 Max Macbook. #3. The release also features a Python package for converting Stable Diffusion models from PyTorch to Core ML using Stable Diffusion v1 refers to a specific configuration of the model architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet and CLIP ViT-L/14 text encoder for the diffusion model. The M1 Ultra has a max power consumption of 215W versus the Stable Diffusion V2. u/mattbisme suggests the M2 Neural are a factor with DT (thanks). Join the Discord to discuss the project, get support, see announcements, etc. ckpt) Stable Diffusion 2. Dec 18, 2022 · Posted18 Dec 2022. g. For the exact same workflow both both i'm seeing around 7. 5 (download link: v1-5-pruned-emaonly. source venv/bin/activate. It appears that the mlx framework, particularly LLaMA and Stable Diffusion, demands significant memory and processing resources, making it challenging to run efficiently on machines with 16GB of RAM, such as the M1 Pro. 23 ~ 30s on iPhone 13 Pro. Here I’m trying it out on a MacBook (though the code also works on iPhones and Sep 13, 2022 · Note: various enterprising individuals have gotten the Stable Diffusion model running on AMD/ATI GPU's, as well as on the built-in GPU of the Apple M1 chip. Feb 15, 2024 · Then, whenever I want to run forge, I open up the Teriminal window, enter “cd stable-diffusion-webui-forge”, “git pull” to update it, and “. 5 Inpainting (sd-v1-5-inpainting. 5. The benchmark table is as below. The system will automatically swap if it needs to, but performance will degrade significantly when it does. Stable Diffusion 1. Recently (around 14 December 2022), Apple’s Machine Learning Research team published “Stable Diffusion with Core ML on Apple Silicon” with Python and Swift source code optimized for Apple Silicon (M1/M2) on Github apple/ml-stable-diffusion. 5 between A1111 and Forge. a picture is rendered in DrawThings or Swift Core ML Diffusers? There is already e. Thanks to Apple engineers, you can now run Stable Diffusion on Apple Silicon using Core ML! This Apple repo provides conversion scripts and inference code based on 🧨 Diffusers, and we love it! To make it as easy as possible for you, we converted the weights ourselves and put the Core ML versions of the models in the Hugging Face Hub. Right click "ldm" and press "New Folder". À voir aussi : Comment installer Llama CPP (Meta) en local sur un Mac (Apple Silicon M1) Avec l Stable DIffusion 1. A diffusion model, which repeatedly "denoises" a 64x64 latent image patch. No dependencies or technical knowledge needed. Install Python V3. Activate the virtualenv just created. 1 require both a model and a configuration file, and image width & height will need to be set to 768 or higher when generating May 26, 2023 · My very first YouTube video#Stable diffusion#MacOS#MacBook Air #M series #AI#Model Sep 3, 2023 · How to install Diffusion Bee and run the best Stable Diffusion models: Search for Diffusion Bee in the App Store and install it. I convert Stable Diffusion Models DreamShaper XL1. Stable DiffusionではRTXやGTXなどのNVIDIAのグラボがよく使われており、高画質かつ大量の画像を高速に出力できてしまいます。. A decoder, which turns the final 64x64 latent patch into a higher-resolution 512x512 image. Diffusion Nov 11, 2022 · I ran stable diffusion on my Apple Silicon M1 Max MacBook Pro using a project called Diffusion Bee. All measurements were taken in production using this serverand load testing app. 2022/08/24. 10. a thread related to that here too. 09 seconds for batch size 1 on A10. With its custom ARM architecture, Apple's latest chipsets unleash exceptional performance and efficiency that, when paired with Stable Diffusion, allows for Feb 9, 2023 · Stable Diffusion is a memory hog, and having more memory definitely helps. They also didn’t check any of the ‘optimized models’ that allow you to run stable diffusion on as little as 4GB of VRAM. This repository is a fork of Stable Diffusion with additional convenience Dec 2, 2022 · Following the optimisations, a baseline M2 Macbook Air can generate an image using a 50 inference steps Stable Diffusion model in under 18 seconds. If you anticipate using Stable Diffusion for more advanced tasks in the future, investing in a GPU with ample VRAM and computational power is recommended. x, SD2. 初回起動時は少し時間がかかるので注意してください。. This approach aims to align with our core values and democratize access, providing users with a variety of options for scalability and quality to best meet their creative needs. Generate images locally and completely offline. RTX NVIDIA GPUs are the only GPUs natively supported by Stable Sep 25, 2022 · Stable Diffusion consists of three parts: A text encoder, which turns your prompt into a latent vector. Feb 22, 2024 · The Stable Diffusion 3 suite of models currently ranges from 800M to 8B parameters. However, newer Apple chips have much Generating a 512x512 image now puts the iteration speed at about 3it/s, which is much faster than the M2 Pro, which gave me speeds at 1it/s or 2s/it, depending on the mood of the machine. Mar 9, 2023 · 本文將分享如何在 M1 / M2 的 Macbook 上安裝 Stable Diffusion WebUI。. definitely not, however i can't wait to see benchmarks that compare say the M1 Max with a specced-out M3 Max. Afterwards whenever you want to run Stable Diffusion you will need to run this. Stable Diffusion is open source, so anyone can run and modify it. This implementation is specifically optimized for the Apple Neural Engine (ANE), the energy-efficient and high-throughput engine for ML inference on Apple silicon. そうすると、自動的にForgeが立ち上がります。. - divamgupta/diffusionbee-stable-diffusion-ui Oct 10, 2022 · Normally, you need a GPU with 10GB+ VRAM to run Stable Diffusion. Which led me to Just posted a YT-video, comparing the performance of Stable Diffusion Automatic1111 on a Mac M1, a PC with an NVIDIA RTX4090, another one with a RTX3060 and Google Colab. Model: Stable Diffusion v2-base, SPLIT_EINSUM attention, CPU + Neural Engine, memory reduction enabled. brew install cmake protobuf rust. 我们也可以更全面的分析不同显卡在不同工况下的AI绘图性能对比。. Average speed for a simple text-to-image generation is around 1. Model: Stable Diffusion v2-base, ORIGINAL attention implementation, running on CPU + GPU. 0 from pyTorch to Core ML. Stable Diffusion. Sep 12, 2022 · Diffusion Bee is billed as the easiest way to run Stable Diffusion locally on an M1 Mac. Oct 5, 2022 · To shed light on these questions, we present an inference benchmark of Stable Diffusion on different GPUs and CPUs. 0 Beta (22A5331f). Clone the Dream Script Stable Diffusion Repository. There were some fun anomalies – like the RTX 2080 Ti often outperforming the RTX 3080 Ti. Extremely fast and memory efficient (~150MB with Neural Engine) Runs well on all Apple Silicon Macs by fully utilizing Neural Engine. STEP1. , sd-v1-4. #1. I found "Running MIL default pipeline" the Pro M2 macbook will become slower than M1. But because of the unified memory, any AS Mac with 16GB of RAM will run it well. x, SDXL, Stable Video Diffusion, Stable Cascade, SD3 and Stable Audio; Asynchronous Queue system; Many optimizations: Only re-executes the parts of the workflow that changes between executions. AMD and Intel cards seem to be leaving a lot of Aug 23, 2022 · M1 MacBook ProでStable Diffusionを動かすまでのメモ. It’s a web interface is run locally (without Colab) that let’s you interact with Stable diffusion with no programm Stable Diffusion 2 (SD2) has been released and the diffusers library already supports it. That’s what has caused the abundance of creations over the past week. 1 on MacOS M1 Pro. 2022/08/23に公開. Reply reply trdcr You’ll be able to run Stable Diffusion using things like InvokeAI, Draw Things (App Store), and Diffusion Bee (Open source / GitHub). Download the model you like the most. 最初 apple/ml-stable-diffusion に従ってPython環境を構築し、モデルを手元で変換して、プログラムを実行して画像を生成していたのですが、めっちゃ簡単な方法を見つけたので 知乎专栏提供一个自由表达和随心写作的平台。 Apr 17, 2023 · Dans cet article, nous vous présenterons un guide étape par étape pour installer et utiliser Stable Diffusion sur votre Mac. Feb 27, 2024 · The synergy between Apple's Silicon technology and Stable Diffusion's capabilities results in a creative powerhouse for users looking to dive into AI-driven artistry on their M1/M2 Macs. tech. Sep 12, 2022 · Sep 11, 2022. Those are the absolute minimum system requirements for Stable Mar 12, 2024 · ターミナルで『stable-diffusion-webui-forge』フォルダまで移動して、下記のコマンドを実行してください。. Increasing the adoption of on-device ML A Modular Stable Diffusion Web-User-Interface, with an emphasis on making powertools easily accessible, high performance, and extensibility. Get TG Pro: https://www. 画像生成AIのStable Diffusionがオープンソースとして公開されましたね。. Lincoln Stein’s ”Stable Diffusion Dream Script” with “for-dummies” installation guides for Windows, Linux and macOS and examples of major features. Back then though I didn't have --upcasting-sampling Apple's Core ML Stable Diffusion implementation to achieve maximum performance and speed on Apple Silicon based Macs while reducing memory requirements. We would like to show you a description here but the site won’t allow us. 5 (v1-5-pruned-emaonly. 4 ( sd-v1-4. I've got the lstein (now renamed) fork of SD up and running on an M1 Mac Mini with 8 GB of RAM. Apr 14, 2023 · この記事では、M1とRTX搭載のPCとでStable Diffusionの比較をしていきます。. Stable Diffusion is a text-to-image model that generates photo-realistic images given any text input. 6. We performed Stable Diffusion text-to-image generation of the same prompt for 50 inference steps, using a guidance scale of 7. It will help developers minimize the impact of their ML inference workloads on app memory, app responsiveness, and device battery life. I was too lazy to install Anaconda / miniconda, so Jul 19, 2023 · As already stated, I’m using Mac M2 for running the Stable Diffusion Model, it is imporant that we assign device to mps. 5 it/s on the RTX3060 12GB compared While running locally on an M1 Pro is nice, recently I've switched over to a Runpod[0] instance running Stable Diffusion instead. I copied his settings and just like him made a 512*512 image with 30 steps, it took 3 seconds flat (no joke) while it takes him at least 9 seconds. Run Stable Diffusion on Apple Silicon with Core ML. #fooocus #stablediffusion #amdgpu #macbooks #apple 👉ⓢⓤⓑⓢⓒⓡⓘⓑⓔ 👉 updates: For Apple M p Going forward --opt-split-attention-v1 will not be recommended. /webui. Highly accessible: It runs on a consumer grade laptop/computer. You need Python 3. Follow the Feature Announcements Thread for updates on new features. Nov 27, 2023 · Some recent innovations have improved the performance of Stable Diffusion derived models on M-series (M1/M2/M3) macs: First, distillation has resulted in models like Segmind’s SSD-1B which is “50% smaller and 60% faster”. On my previous Mac mini I tried different settings and commands, with no increase whatsoever so I don't think there is a way right now to achieve a better Sep 4, 2022 · python3 -m virtualenv venv. NVIDIA製のグラボを積んだWindowsマシンよりは遅いですが、M1 Macの醍醐味はその Dec 17, 2022 · Out of the foundational models, Stable Diffusion v1. I'm expecting much improved performance and speed. It's slow but it works -- about 10-20 sec per iteration at 512x512. 1 require both a model and a configuration file, and image width & height will need to be set to 768 or higher when generating images: Automatic 1111 is a game changer for me. (around 14s for 20 steps). In the AI field, Nvidia with their CUDA Cores is simply too far ahead as of now. 1 require both a model and a configuration file, and image width & height will need to be set to 768 or higher when generating Mar 31, 2022 · Apple achieved this misleading comparison by cutting off the graph before the Nvidia GPU got anywhere close to its maximum performance. Otherwise here is some info on running Facebook’s LLaMa or Alpaca - including performance or RAM usage. Second, rather than having to painfully convert models to Apple’s CoreML format, like I did back in December 2022, a Sep 16, 2022 · Before beginning, I want to thank the article: Run Stable Diffusion on your M1 Mac’s GPU. Expand "models" by clicking on it, then expand "ldm". tunabellyso Performance (after the initial generation, which is slower) ~8s in macOS on MacBook Pro M1 Max (64 GB). 4 to 2. Second, rather than having to painfully convert models to Apple’s CoreML format, like I did back in December 2022, a Sep 16, 2022 · Any-Winter-4079’s “StableDiffusion RUNS on M1 chips” Reddit post for even more things to try like img2img and upscaling Dr. AI. ckpt) Stable Diffusion 1. Apr 5, 2023 · Et voila, vous savez désormais comment installer et utiliser Stable Diffusion 1. Here are some results. Once the installation is complete, activate the virtualenv by running this code. Learn more about it on the official Pytorch docs. 0 and 2. If not, proceed the STEP2. Yeah, Midjourney is another good service but so far, WebUI with Stable Diffusion is the best. High-performance image generation using Stable Diffusion in KerasCV with support for GPU for Macbook M1Pro and M1Max. All rights belong to its creators. Step 2: Double-click to run the downloaded dmg file in Finder. Dec 7, 2023 · alikhan-tech commented on Dec 8, 2023. First, your text prompt gets projected into a latent vector space by the Aug 29, 2023 · A comparison of running Stable Diffusion Automatic1111 on - a Macbook Pro M1 Max, 10 CPU / 32 GPU cores, 32 GB Unified Memory- a PC with a Ryzen 9 and an NVI We would like to show you a description here but the site won’t allow us. The HuggingFace upgrade has support for 768x768 higher resolution In the app, open up the folder that you just downloaded from github that should say: stable-diffusion-apple-silicon On the left hand side, there is an explorer sidebar. 1 require both a model and a configuration file, and the image width & height will need to be set to 768 or higher when generating images: Stable Diffusion 2. With its custom ARM architecture, Apple's latest chipsets unleash exceptional performance and efficiency that, when paired with Stable Diffusion, allows for May 26, 2023 · You ask on performance of »certain AI tasks« which you seem to equal to models - you just want to know how fast e. 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. I'm sure there are windows laptop at half the price point of this mac and double the speed when it comes to stable diffusion. Comes with a one-click installer. We've seen Stable Diffusion running on M1 and M2 Macs, AMD cards, and old NVIDIA cards, but they tend to be difficult to get running and are more prone to problems. To install custom models, visit the Civitai "Share your models" page. I made my article by adding some information to that one. sh” to run it. 5 Inpainting ( sd-v1-5-inpainting. 1件. These are our findings: Many consumer grade GPUs can do a fine job, since stable diffusion only needs about 5 seconds and 5 GB of VRAM to run. sh file I posted there but I did do some testing a little while ago for --opt-sub-quad-attention on a M1 MacBook Pro with 16 GB and the results were decent. Performance has not been up to Nvidia Mar 17, 2022 · Apple’s UltraFusion interconnect technology here actually does what it says on the tin and offered nearly double the M1 Max in benchmarks and performance tests. Nov 9, 2022 · How to speed up your Stable Diffusion inference and get it running as fast as possible on your M1Pro Macbook Pro laptop. Open Diffusion Bee and import the model by clicking on the "Model" tab and then "Add New Model. The model and the code that uses the model to generate the image (also known as inference code). We recommend you use attention slicing to reduce memory pressure during inference and prevent swapping, particularly if your computer has lass than 64 GB of system RAM, or if you 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. Dec 13, 2023 · Results show that the M1 Pro chip doesn't quite meet the Nvidia GPU's performance, taking 216 seconds to process the audio compared to the 4090's 186 seconds. Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. 10 or higher. Register on Hugging Face with an email address. Firstly, install the following: python3 -m pip install virtualenv python3 -m virtualenv venv. I found the macbook Air M1 is fastest. M1/M2 performance is very sensitive to memory pressure. It's a one-click installer hosted on GitHub that runs Stable Diffusion locally on the computer. Jan 21, 2023. Step 1: Go to DiffusionBee’s download page and download the installer for MacOS – Apple Silicon. 40 it/sec. Yes 🙂 I use it daily. Hey, is there a tutorial to run the latest Stable Diffusion Version on M1 chips on MacOS? I discovered DiffusionBee but it didn't support V2. Made by Thomas Capelle using W&B Jan 21, 2023 · 1,589. 4 (sd-v1-4. 如果你從來沒有接觸過 Stable Diffusion. I don't know exactly what speeds you'll get exactly with the webui-user. 5 ( v1-5-pruned-emaonly. MPS device enables high-performance training on GPU for MacOS devices with Metal programming framework. Jan 26, 2024 · run stable diffusion Fooocus on Macbook (with AMD GPU or M1 M2 M3). It really depends on the native configuration of the machine and the models used, but frankly the main drawback is just drivers and getting things setup off the beaten path in AMD machine learning land. What makes Stable Diffusion unique ? It is completely open source. 这次我们给大家 Performance These are the results we got on a M1 Max MacBook Pro with 64 GB of RAM, running macOS Ventura Version 13. The increase in speed is due to more powerful hardware (from M1/8GB to M2 Pro/16GB). Install the latest version of Python: $ python3 -V. なので非常にNVIDIAのグラボが人気なのですが、そのほかの Jul 10, 2023 · The Stable Diffusion community has worked diligently to expand the number of devices that Stable Diffusion can run on. As well as generating predictions, you can hack on it, modify Dec 1, 2022 · タイトルの通り M1 MacBook Pro で Stable Diffusion を動かしました。今回はあえてローカルで動かしていますが、試すだけであれば Google Colab で動かす方が早くて楽かもしれません:p. 5 is the most popular. For example, generating a 512×512 image at 50 steps on an RTX 3060 . Stable Diffusion 3 combines a diffusion transformer architecture and flow matching. 4’ has helped resolve their errors, so there must be The model file for Stable Diffusion is hosted on Hugging Face. The model was pretrained on 256x256 images and then finetuned on 512x512 images. You can run Stable Diffusion in the cloud on Replicate, but it’s also possible to run it locally. 4 (download link: sd-v1-4. I recently got a great deal on RTX 3060 12GB model and threw it into my windows machine (was previously running a GTX 960 2GB) and tried to run stable diffusion on it. When it comes to speed to output a single image, the most powerful Ampere GPU (A100) is Feb 27, 2024 · The synergy between Apple's Silicon technology and Stable Diffusion's capabilities results in a creative powerhouse for users looking to dive into AI-driven artistry on their M1/M2 Macs. This repository is a fork of Stable Diffusion with additional convenience Jan 24, 2023 · We focused on optimizing the original Stable Diffusion and managed to reduce serving time from 6. Apple duct-taped two M1 Max chips Aug 31, 2022 · Run Stable Diffusion on your M1 Mac’s GPU. The memory consumption reaching around 13GB for LLaMA and 11GB for Stable Diffusion on Feb 22, 2023 · M1 MacでStable Diffusionしたい人が試すときの一番簡単で高速な方法（M1 Mac GPUでの実行）. The main reasons being high workloads placed on the laptop degrade the battery faster and it takes ~40s to render a single image. I also recently ran the waifu2x app (RealESRGAN and more) on my M1 iPad (with 16! GB RAM) and was thoroughly impressed with how well it performed, even with video. Performance (after the initial generation, which is slower) ~8s in macOS on MacBook Pro M1 Max (64 GB). But my 1500€ pc with an rtx3070ti is way faster. 5 & 2. However, to run Stable Difussion on a PC laptop well, you need buy a $4000 laptop with a 3080 Ti to get more than 10GB of VRAM. May 15, 2024 · DiffusionBee is one of the easiest ways to run Stable Diffusion on Mac. Using InvokeAI, I can generate 512x512 images using SD 1. Un guide sera bientôt disponible sur notre site pour apprendre à utiliser Stable Diffusion plus en détail. UPDATE: 29 Sept – Some people have shared that using ‘pip install protobuf==3. 5 in about 30 seconds… on an M1 MacBook Air. A dmg file should be downloaded. 今回はM1のものととi5の第8世代のものの2つで検証します。. 1 or V2. Ideally an SSD. Download the latest model file (e. Though Apple Silicon is faster than AMD GPUs at least. In this article, I’ll start at the beginning: cloning the mlx-examples repo, and running the Stable Diffusion model via Feb 4, 2024 · To assess the performance and efficiency of AMD and NVIDIA GPUs in Stable Diffusion, we conducted a series of benchmarks using various models and image generation tasks. Hope it's helpful! In the AI field, Nvidia with their CUDA Cores is simply too far ahead as of now. I own these machines, so I can give you an insight into my personal experiences, benchmarks, pricing and more. That being said, I haven’t seen any significant difference in terms of performance using SD1. Name "New Folder" to be "stable-diffusion-v1" Aug 28, 2023 · Stable Diffusion的发展非常迅速，短短不到一年的时间，它能实现的功能也是越来越多，国内社区的发展也是越来越成熟，国内模型作者带来的底模和Lora等数量也是越发丰富。. GMGN said: I know SD is compatible with M1/M2 Mac but not sure if the cheapest M1/M2 MBP would be enough to run? According to the developers of Stable Diffusion: Stable Diffusion runs on under 10 GB of VRAM on consumer GPUs, generating images at 512x512 pixels in a few seconds. 首先會提供一些 Macbook 的規格建議，接著會介紹如何安裝環境，以及初始化 Stable Diffusion WebUI。. qh kg bt fo zp yc bf yj na qq