sd-akashic  by Maks-s

Stable Diffusion resource compendium

created 3 years ago
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Project Summary

This repository serves as a comprehensive compendium of information, studies, art styles, and tools related to Stable Diffusion (SD). It aims to guide users, from beginners to researchers, through the exploration of SD's capabilities, offering resources for understanding its generation process, prompt engineering, and various implementation methods.

How It Works

The compendium categorizes information into distinct sections: General Studies, Art Styles/Artist Lists, Keyword Lists, and Prompts. It employs a nomenclature system using colored diamonds to differentiate resources based on SD, other AI imagery tools, or no AI imagery. This structured approach allows users to quickly identify relevant information and understand the context of each resource.

Quick Start & Requirements

This repository is a curated collection of links and information, not a runnable application. Users will need to follow the links provided to access specific tools, guides, or models, many of which may have their own installation and hardware requirements (e.g., Python, specific forks of SD, HuggingFace Spaces, Colab notebooks).

Highlighted Details

  • Extensive lists of guides covering beginner to advanced topics, including installation, prompt engineering, and specific techniques like seed editing.
  • A wide array of links to various Stable Diffusion implementations, UIs, and plugins for different platforms (e.g., AUTOMATIC1111, InvokeAI, Krita, Blender).
  • Detailed studies on modifiers (CFG, samplers, steps) and keywords, providing empirical data on their impact on image generation.
  • Curated lists of art styles, artists, and keywords known to work well with text-to-image models.

Maintenance & Community

The repository is maintained by Maks-s and appears to be community-driven, with numerous contributions cited from Discord users and specific GitHub forks. Links to community resources like Discord servers or specific user handles are provided within the studies.

Licensing & Compatibility

The repository itself is a collection of links and information, and thus does not have a specific license. However, the underlying Stable Diffusion models and associated tools linked within will have their own licenses, which users must adhere to. Compatibility will vary based on the specific tools and models accessed.

Limitations & Caveats

The repository is a static collection of links and information; it does not provide direct functionality. Users must navigate external resources, which may change or become deprecated. The README warns that running untrusted .ckpt and .pt files can be malicious.

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Last commit

2 years ago

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