Civitai with Stable Diffusion Automatic 1111 (Checkpoint, LoRa Tutorial)

14 Jul 202322:40

TLDRThis video tutorial offers a comprehensive guide on utilizing Civic AI models with Stable Diffusion, an open-source imaging model. It covers essential extensions and settings for optimal use, introduces various Civic AI models like checkpoints and textual inversions, and provides step-by-step instructions for installation and usage. The tutorial also shares tips on leveraging the PNG info feature for effective prompting, demonstrating how to generate high-quality images without additional costs.


  • ๐Ÿ–ผ๏ธ The video discusses the use of Stable Diffusion, an open-source model for generating images, running locally on a PC.
  • ๐Ÿš€ To achieve high-quality images, one must utilize the full potential of the local installation of the Automatic Double One (AD1) software.
  • ๐Ÿ“Œ The video provides essential extensions and settings necessary for using Civic AI models effectively.
  • ๐Ÿ” Different Civic AI models, including checkpoints, textual inversions, hypernetworks, Laura, Lycorus, and wildcards, are explained.
  • ๐Ÿ”— The tutorial guides on how to install and use Civic AI models with a local Stable Diffusion setup.
  • ๐Ÿ“‚ Properly organizing downloaded models into specific folders like checkpoints, embeddings, hypernetworks, and others is crucial.
  • ๐Ÿ› ๏ธ The use of extensions like Chorus and Wildcards is detailed, with links provided in the video description for installation.
  • ๐ŸŒ The video creator demonstrates how to safely browse and select models on the Civic AI website.
  • ๐ŸŽจ The process of generating images is showcased, including tips on how to adjust prompts and settings for desired outputs.
  • ๐Ÿ’ก The PNG info feature on Stable Diffusion is highlighted as an easy way to learn model prompts and parameters.
  • ๐Ÿค– The importance of hardware capabilities is emphasized for running heavier models and achieving optimal results with Stable Diffusion.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about using Stable Diffusion, an open-source model, for generating high-quality images on a personal computer without any additional costs.

  • What are some of the images that can be created using Stable Diffusion?

    -Images that can be created using Stable Diffusion include realistic depictions of celebrities, superheroes, and architectural designs.

  • What is the significance of the open-source nature of Stable Diffusion?

    -The open-source nature of Stable Diffusion allows many creators to experiment with it and generate new models, leading to a wider variety of high-quality images.

  • What are the essential extensions and settings needed to use Civic AI models with Stable Diffusion?

    -The essential extensions and settings include installing Stable Diffusion up to version 2, the Ultimate SD extension for upscaling images, and using xformers to optimize image generation and reduce VRAM usage.

  • How can one acquire and use Civic AI models?

    -Civic AI models can be acquired by downloading them from the Civic AI website and placing them in the appropriate directories within the Stable Diffusion folder, such as the models, embeddings, hypernetworks, Laura, and wildcards folders.

  • What is the role of the PNG info feature in Stable Diffusion?

    -The PNG info feature in Stable Diffusion allows users to view and understand the parameters and settings used for a particular image, which can be helpful for learning how to create similar images using the model prompts.

  • How does one resolve errors encountered when using Civic AI models with Stable Diffusion?

    -Errors can be resolved by identifying the missing components or settings from the image prompt, searching for the required upscalers or other elements online, and downloading and installing them in the correct directories.

  • What are some tips for using prompts effectively with Stable Diffusion?

    -Effective prompt usage involves making minor changes to the prompt while paying attention to the model training, being careful with the wording as the models are trained with specific prompts, and using the PNG info method to understand and replicate settings and parameters.

  • What types of images can be generated using the different Civic AI models?

    -Using Civic AI models, one can generate a wide range of images including comic book art, anime, realistic portraits, landscapes, science fiction scenes, macro photography, and gaming assets.

  • What hardware requirements should one consider when using Stable Diffusion?

    -When using Stable Diffusion, one should have good hardware, particularly a GPU with a significant amount of VRAM, especially for heavier models that require more resources.

  • How can users learn and practice using Stable Diffusion further?

    -Users can practice by downloading and experimenting with the 50 images provided in the video description through the PNG info method, which allows them to understand the settings and parameters used in generating those images.



๐Ÿ–ผ๏ธ Introduction to Stable Diffusion and Civic AI Models

This paragraph introduces the viewer to the capabilities of Stable Diffusion, an open-source model for generating images, and Civic AI models. The speaker showcases various images created using the software, including realistic depictions of celebrities, superheroes, and architectural designs. The paragraph emphasizes the potential of using these tools without incurring additional costs and sets the stage for a tutorial on optimizing the local installation of Stable Diffusion and understanding the different Civic AI models like checkpoints and textual inversions.


๐Ÿ› ๏ธ Installation and Setup of Extensions for Stable Diffusion

The speaker provides a step-by-step guide on how to prepare the user's system for using Civic AI models with Stable Diffusion. This includes installing the latest version of Stable Diffusion, upscaling images with the Ultimate SD extension, and setting up exformers to optimize image generation and reduce VRAM usage. The paragraph also covers updating the PIP version and troubleshooting potential errors related to upscalers, showcasing the process of downloading and installing necessary components for seamless image generation.


๐ŸŒ Exploring Civic AI Models and Their Applications

In this paragraph, the focus shifts to exploring Civic AI models and their applications. The speaker explains the different types of models available, such as checkpoints, textual inversions, hypernetworks, and wildcards, and where they should be placed in the file directory. The speaker also demonstrates how to use these models to generate images by downloading and applying them in Stable Diffusion, highlighting the versatility and ease of use in creating a variety of images based on different prompts and settings.


๐ŸŽจ Customizing Prompts and Image Generation with Civic AI

The speaker delves into the process of customizing prompts and generating images using Civic AI models. This includes making adjustments to the prompts, such as changing the portrait of a girl or the setting of a scene, and experimenting with different parameters to achieve desired results. The paragraph also touches on the importance of understanding the requirements of each model, such as specific upscalers or control settings, and how to troubleshoot and adapt to these needs for optimal image generation.


๐Ÿ“š Conclusion and Additional Resources for Image Generation

The speaker concludes the tutorial by summarizing the key points covered in the video and offering additional resources for further exploration. The paragraph emphasizes the ease and accessibility of creating a wide range of images using Stable Diffusion and Civic AI models, and provides tips for users experiencing hardware limitations. The speaker also shares a link to a collection of images that viewers can use to practice the PNG info method, encouraging continued learning and experimentation.



๐Ÿ’กStable Diffusion

Stable Diffusion is an open-source model used for generating images. It is mentioned in the video as the primary tool for creating various types of images, from realistic portraits to architectural designs, without incurring additional costs. The video provides a tutorial on how to optimize the use of Stable Diffusion on a personal computer, including the installation of extensions and settings for better performance.

๐Ÿ’กOpen Source Model

An open-source model refers to a software model whose source code is made publicly available, allowing others to view, use, modify, and distribute the model. In the context of the video, Stable Diffusion is an open-source model that many creators are using and modifying to generate new models and images. This openness enables a collaborative environment where the model can be continuously improved and customized by the community.


In the context of the video, extensions refer to additional software components that enhance or add new functionalities to a primary software application. The video specifically talks about essential extensions needed for using Civic AI models with Stable Diffusion, such as xformers and the Ultimate SD extension for upscaling images. These extensions are crucial for optimizing the performance and output of the image generation process.

๐Ÿ’กCivic AI Models

Civic AI models are a set of tools or models that users can utilize with the Stable Diffusion software to generate specific types of images. These models include checkpoints, textual inversions, hypernetworks, Laura, lycorus, and wildcards, each serving different functions and requiring specific handling and installation procedures. The video provides guidance on understanding and using these Civic AI models effectively with Stable Diffusion.


Checkpoints in the context of the video are base models used in the image generation process with Civic AI. They are typically larger files, averaging between two to six gigabytes in size, and are also referred to as dream Booth models. Checkpoints serve as the foundation for generating images with specific styles or characteristics.

๐Ÿ’กTextual Inversions

Textual inversions are smaller models in the Civic AI suite that require a checkpoint model to function. They are used to manipulate the text-based instructions for image generation, allowing for more specific control over the output. Textual inversions are saved in the embeddings directory and are used alongside a base model to refine the image generation process.


Hypernetworks are a type of Civic AI model that, like textual inversions, are designed to be used with a checkpoint base model. They are used to adjust the settings of the image generation process, providing additional control over the final output. Hypernetworks are saved in a specific directory within the model folder and can be adjusted using the strength slider in the web UI settings.


Upscaling refers to the process of increasing the resolution of an image while maintaining or improving its quality. In the video, upscaling is discussed as a technique to enhance the quality of images generated by Stable Diffusion. The use of extensions like the Ultimate SD extension is mentioned to perform upscaling, which is important for achieving high-quality results from the image generation process.

๐Ÿ’กPNG Info

PNG Info is a feature in Stable Diffusion that allows users to view detailed information about an image, including parameters and EXIF comments. This feature is used to understand the settings and parameters that led to the generation of a particular image, which can then be replicated or modified for new image generation attempts. The PNG Info method is presented in the video as an easy way to learn and apply model prompts for generating images.


Prompting in the context of the video refers to the process of providing text-based instructions or descriptions to the Stable Diffusion model to guide the generation of specific images. Prompts can include details about the desired image's content, style, or other characteristics. The video provides tips and tricks on crafting effective prompts and using the PNG Info feature to understand and modify prompts for better image generation results.


Introduction to stable diffusion, an open source model for generating high-quality images.

Explaining the importance of using the local install of automatic double one to fully utilize the potential of stable diffusion.

Essential extensions and settings required for using Civic AI models with stable diffusion.

Explanation of different Civic AI models, including checkpoints, textual inversions, hypernetworks, Laura, lycorus, and wildcards.

A step-by-step guide on installing and using the ultimate SD extension for upscaling images.

Optimizing image generation and reducing VRAM usage with the useformer tool.

Updating the PIP version and its significance in the overall process.

Importing and using checkpoint models, such as dreamshaper, for creating various styles of images.

Utilizing the PNG info feature on stable diffusion for easier learning of model prompts.

Demonstration of how to adjust settings and parameters for generating desired images using Civic AI models.

Addressing common errors and their solutions, such as finding the right upscaler or adjusting settings based on the model's requirements.

The process of experimenting with prompts to achieve specific outcomes, like changing the portrait of an Indian girl to an American girl with pink hair.

Exploring the capabilities of 3D rendering styles with the Lora model and riff animated checkpoint.

The importance of using specific prompts as trained by Civic AI models for successful image generation.

Conclusion emphasizing the ease of creating amazing images with stable diffusion and the technical know-how provided in the video tutorial.

Offering a zip link with 50 images for practice using the PNG info method.