Install Stable Diffusion Locally (Quick Setup Guide)

In this informative video, the host provides a comprehensive guide on how to install and operate Stable Diffusion, a powerful AI art tool, both locally on a PC and in the cloud for those with older computers or Macs. The local installation offers unlimited creative potential, free from restrictions found on online platforms, and allows for the use of custom-trained images. The video outlines the process of setting up Stable Diffusion using Hugging Face and GitHub, installing necessary software, and downloading the required AI models. It also offers an alternative cloud-based solution through Run Diffusion, which, for a small fee, provides access to high-performance GPUs for seamless AI art generation. The host encourages viewers to experiment with various settings and models to unlock the full creative potential of Stable Diffusion, promising more in-depth explorations of the tool in future content.

Takeaways

• 💡 **Local Installation Advantages**: Having Stable Diffusion installed on your PC allows for unrestricted content creation, including using your own trained images and generating any type of AI art without limitations.
• 🚀 **Control Net Features**: Local installations enable access to advanced features like pose modeling, scribble control, image-to-image transformations, and text-based image tweaking.
• 📚 **Video Generation**: With local setup, you can utilize tools like Deforum, a video generator that uses Stable Diffusion to create impressive videos.
• 🖥️ **System Requirements**: To install Stable Diffusion locally, you need a PC with a decent graphics card. For those with older computers or Macs, a cloud-based alternative is provided.
• 🌐 **Cloud Alternative**: The cloud service, rundiffusion.com, offers an alternative to local installation, allowing users to run Stable Diffusion on cloud-based GPUs for a fee.
• 📝 **Account Creation**: Before starting the installation, create a free account on huggingface.co and GitHub, which are necessary for accessing and managing the Stable Diffusion models and files.
• 🔗 **Downloading Stable Diffusion Files**: Download the Stable Diffusion files from hugging face, with the option to choose between different models like 1.4, 1.5, and 2.1.
• 🔍 **Python Installation**: Install Python on your computer, with the latest stable release recommended for the best compatibility with Stable Diffusion.
• 📂 **File Management**: Organize your files by creating a dedicated 'AI' folder and placing the downloaded Stable Diffusion files in the appropriate subfolders.
• ⏱️ **Script Execution**: Running the 'web ui-user.bat' file initiates a series of scripts that may take up to 30 minutes to complete, after which you can access the Stable Diffusion interface.
• 🎨 **Image Generation**: Once Stable Diffusion is running, you can generate images with various settings, such as batch size, sampling methods, and CFG scales, to achieve different styles and outcomes.

Q & A

What is the main purpose of installing Stable Diffusion locally?

The main purpose of installing Stable Diffusion locally is to have zero limits on the type of content you can create, allowing for full customization and control over the AI art generation process.

Why might someone want to run Stable Diffusion in the cloud?

Running Stable Diffusion in the cloud is an alternative for those with older computers or on a Mac, providing the same benefits as a local install without the need for a powerful local GPU.

What are the benefits of having Stable Diffusion installed locally compared to using it through an online platform like Midjourney?

Local installation allows for unrestricted content creation, including not safe for work content and the use of words like 'blood' in images. It also enables the use of custom trained images and advanced features like ControlNet, scribble control, and video generation.

What are the system requirements for installing Stable Diffusion locally?

To install Stable Diffusion locally, you need a PC with a decent graphics card. For those without a suitable PC or a Mac, an alternative cloud-based solution is provided.

How does one begin the process of installing Stable Diffusion locally?

The process starts by creating a free account on huggingface.co and GitHub, then downloading and installing Git for Windows. After that, a new folder is created on the hard drive, and the user follows a series of commands in the Git Bash to clone the Stable Diffusion Web UI.

What is the role of the 'get-bash' in the installation process?

The 'get-bash' is a command-line interface used to execute commands for downloading and setting up the Stable Diffusion Web UI and other necessary components.

What is the significance of downloading the Stable Diffusion files from Hugging Face?

Downloading the Stable Diffusion files from Hugging Face is essential as these files contain the model weights necessary for the AI to generate images. Different versions of the model (1.4, 1.5, 2.1) are available to experiment with.

How does one integrate their own trained images into Stable Diffusion?

If you have a trained model from a previous tutorial, such as training your face into the AI, you can place the ckpt file generated from that process into the 'models' folder within the Stable Diffusion Web UI directory to use it for image generation.

What is the alternative cloud-based solution for running Stable Diffusion?

The alternative cloud-based solution is called 'Run Diffusion', which is accessible at rundefusion.com. It allows users to run Stable Diffusion on cloud-based GPUs and computers, bypassing the need for local installation.

What are the different GPU options available on Run Diffusion, and how do they differ?

Run Diffusion offers three different GPU options: one at 50 cents per hour, another at 99 cents per hour, and the most expensive at $1.75 per hour. The main difference between these options is the speed at which they generate images, with the more expensive options being faster.

How does the process of generating images with Stable Diffusion on Run Diffusion compare to a local installation?

The process is quite similar, with the main difference being that the computation is done on Run Diffusion's servers rather than the user's local machine. This means that users can access the same features and model versions without the need for a powerful local GPU.

Outlines

00:00

🚀 Introduction to Setting Up Stable Diffusion

The video begins with an introduction to setting up Stable Diffusion, a powerful AI art tool, on a PC or in the cloud. The host outlines the benefits of local installation, such as zero limits on content creation, the ability to use custom trained images, and access to advanced features like ControlNet and image-to-image generation. The process starts with creating accounts on Hugging Face and GitHub, followed by downloading and installing necessary software and models.

05:01

💻 Installing Stable Diffusion Locally

The host provides a step-by-step guide to installing Stable Diffusion locally on a PC. This includes creating a folder for the AI, using Git Bash to clone the Stable Diffusion Web UI, and downloading the Stable Diffusion model files from Hugging Face. The video also covers installing Python and setting up the Web UI to generate images with various parameters and models, emphasizing the flexibility and customization available to users.

10:02

🌐 Alternative Cloud-Based Setup with Run Diffusion

For those without a capable PC or GPU, the host introduces Run Diffusion, a cloud-based alternative that allows users to run Stable Diffusion on rented GPU time. The host demonstrates how to sign up, select GPU options based on speed and cost, and start a session to access a cloud-based Stable Diffusion interface. The cloud option is highlighted as a convenient and cost-effective way to access the full capabilities of Stable Diffusion without the need for local hardware.

🎨 Exploring Creative Possibilities with Stable Diffusion

The host concludes by discussing the creative potential unlocked by having Stable Diffusion installed locally or running on a cloud GPU. They mention the ability to generate any type of image without restrictions and the various settings that can be adjusted for different results. The host expresses excitement about future videos that will explore more advanced features and tools, encouraging viewers to subscribe for updates and check out additional AI tools on their curated website, Future Tools.

Keywords

Stable Diffusion

Stable Diffusion is an AI model designed for generating images from textual descriptions. It is a significant tool in the field of AI art, allowing users to create a wide range of images without restrictions when installed locally. In the video, it is the central technology that the host demonstrates how to install and use for creating various types of AI-generated images and videos.

Local Installation

Local installation refers to the process of installing and running software, like Stable Diffusion, directly on a user's personal computer rather than using it online or via cloud services. The video emphasizes the benefits of having Stable Diffusion installed locally, such as having no content restrictions and the ability to use personalized trained images.

Hugging Face

Hugging Face is a company that provides a platform for developers to share and collaborate on AI models, including Stable Diffusion. In the context of the video, the host instructs viewers to create an account on Hugging Face to download the Stable Diffusion model files necessary for the local installation process.

GitHub

GitHub is a web-based platform primarily used for version control and collaboration in software development. The video script mentions GitHub as a place where viewers need to sign up for an account, which will be used in conjunction with Hugging Face to manage the AI model and its dependencies.

Graphics Card

A graphics card, also known as a GPU (Graphics Processing Unit), is a type of computer hardware that renders images, video, and animations. The video mentions the need for a 'decent graphics card' for running Stable Diffusion locally, as it is essential for the computationally intensive process of generating images from text descriptions.

ControlNet Features

ControlNet features refer to a set of tools that allow users to have more control over the AI-generated images, such as posing models or modifying specific aspects of an image based on textual instructions. The video discusses how having Stable Diffusion installed locally enables access to these advanced features, which are not available in all online versions of the software.

Python

Python is a high-level programming language widely used in the development of AI applications. In the video, the host instructs viewers to install Python on their computers as part of the preparation for running Stable Diffusion, highlighting its importance as a prerequisite for the software's operation.

Run Diffusion

Run Diffusion is an alternative cloud-based service mentioned in the video for users who do not have a PC or a powerful enough GPU to run Stable Diffusion locally. It allows users to rent time on a cloud GPU to run the AI model, bypassing the need for local installation and hardware requirements.

Web UI (User Interface)

Web UI, short for Web User Interface, is the interface through which users interact with the Stable Diffusion model. The video details the process of setting up the Web UI for Stable Diffusion, which is essential for users to input text descriptions and generate images.

Batch Size

Batch size in the context of AI image generation refers to the number of images the model generates in one go when processing a request. The video script describes adjusting the batch size, which can affect the speed and quantity of image generation.

Sampling Methods

Sampling methods are the algorithms used by the AI to generate images from text. Different methods can produce varying styles and qualities of images. The video discusses experimenting with different sampling methods like DDIM (Denoising Diffusion Implicit Models) to achieve desired results.

Highlights

The video provides a quick setup guide for installing and running Stable Diffusion locally on a PC or in the cloud for those with older computers or Macs.

Local installation of Stable Diffusion offers zero limits on content creation, including the ability to create not safe for work content and use restricted words.

With local installation, users can integrate their own trained images into Stable Diffusion for personalized content generation.

The video demonstrates how to use control net features for pose modeling and scribble control network for drawing realistic versions of images.

Local installation enables the use of image-to-image and instruct picks for text-guided image manipulation.

Deforum, a video generator using Stable Diffusion, is mentioned as a possibility with local installation.

The process for local installation requires a PC with a decent graphics card and involves creating a Hugging Face and GitHub account.

Get for Windows software is needed, along with creating a new folder on the hard drive for the AI setup.

GitHub repository 'automatic 1111' is used for the Stable Diffusion web UI, which is cloned using the provided URL.

Stable Diffusion files are downloaded from Hugging Face, with the 1.4 original model being recommended for beginners.

Python needs to be installed on the computer, with the latest stable release suggested for the setup.

The Stable Diffusion checkpoint file is placed in the 'models' folder within the Stable Diffusion web UI directory.

The 'web ui-user.bat' script is executed to run various setup scripts, which may take around 30 minutes.

Once the setup is complete, a local URL is provided to access the Stable Diffusion interface in a web browser.

The video suggests experimenting with different sampling steps and methods for varied image generation results.

An alternative cloud-based solution called 'Run Diffusion' is introduced for those without a capable PC or GPU.

Run Diffusion offers different GPU options with varying costs and speeds for image generation.

The video concludes with a teaser for future content exploring advanced features and capabilities of Stable Diffusion.

The presenter invites viewers to subscribe to a newsletter for weekly updates on AI tools and highlights.