New Release: Stable Diffusion 2.1 with GUI on Colab

1littlecoder
7 Dec 202211:29

TLDRStability AI has released Stable Diffusion 2.1, an update to their AI image generation model. The new version addresses concerns about poor anatomy in generated images by altering the training dataset to remove adult content and certain artists. This change has led to improvements in image quality, particularly regarding human anatomy. The video demonstrates how to access and use Stable Diffusion 2.1 through a lightweight GUI on Google Colab, provided by kunash. The user interface allows for easy experimentation with prompts and offers features like text-to-image, image-to-image, in-painting, and upscaling. The video also discusses the reproducibility of results and the importance of sharing detailed prompts for accurate reproduction. The host encourages viewers to try out Stable Diffusion 2.1 and share their findings, especially regarding the model's performance on human anatomy.

Takeaways

  • 🚀 Stable Diffusion 2.1 has been released by Stability AI and is accessible via various methods, including Colab.
  • 🎨 The new version aims to address issues with anatomy and certain keywords not working as expected in previous versions.
  • 🔍 The training dataset has been updated to remove adult content and certain artists, leading to improvements in image quality.
  • 🌐 The announcement post features an impressive image, but the presenter was unable to reproduce it due to lack of detailed reproduction information.
  • 📈 Stability AI has focused on improving reproducibility, which was a challenge in earlier versions.
  • 🖼️ A new user interface (GUI) for Stable Diffusion 2.1 has been made available on GitHub, allowing for easier access and use.
  • 🚀 The GUI is lightweight and can run on Google Colab for free, making it more accessible to users.
  • 🌟 Users have reported positive feedback on the Reddit subreddit, sharing images generated with Stable Diffusion 2.1.
  • 🎭 The new model allows for the generation of celebrity and superhero images, which was a complaint in previous versions.
  • 🔧 The GUI offers various features including text-to-image, image-to-image, in-painting, and upscaling models.
  • 📉 Negative prompts can be used to refine image generation, avoiding unwanted elements like 'cartoonish' in the example provided.
  • ⚙️ For those who prefer not to use a GUI, the diffusers library can be used directly by changing the model ID to access Stable Diffusion 2.1.

Q & A

  • What is the name of the latest release from Stability AI?

    -The latest release from Stability AI is called Stable Diffusion 2.1.

  • Why did Stability AI decide to change the training dataset in Stable Diffusion 2.1?

    -Stability AI changed the training dataset in Stable Diffusion 2.1 to address issues with bad anatomy and to remove adult content and certain artists that were causing problems.

  • How can users access Stable Diffusion 2.1?

    -Users can access Stable Diffusion 2.1 using diffusers, automatic 1.1.1, or through the GitHub repository provided in the video script.

  • What are some of the improvements in Stable Diffusion 2.1 over the previous version?

    -Stable Diffusion 2.1 has improvements in human anatomy and the ability to generate images of superheroes. It also addresses issues with certain keywords and prompts not working as expected.

  • What is the issue with reproducibility that the video mentions?

    -The issue with reproducibility is that the shared prompts do not include the seed value, guidance scale, or number of steps, making it difficult for others to recreate the images.

  • How can users try out Stable Diffusion 2.1 on Google Colab?

    -Users can try out Stable Diffusion 2.1 on Google Colab by visiting the provided GitHub repository, opening the Colab link, connecting, and running the necessary buttons to install dependencies and start the application.

  • What are the different models available in the Stable Diffusion 2.1 GUI?

    -The Stable Diffusion 2.1 GUI offers text-to-image, image-to-image, in-painting, and upscaling models.

  • What is the recommended approach for using prompts with Stable Diffusion 2.1?

    -It is recommended to start with simple prompts and a moderate number of steps, adjusting as needed based on the results. It's also suggested to experiment with different prompts and not rely solely on higher steps for better images.

  • How can users who prefer not to use a GUI access Stable Diffusion 2.1?

    -Users who prefer not to use a GUI can access Stable Diffusion 2.1 directly from the diffusers Library by changing the model ID and installing stable diffusers from GitHub.

  • What is the significance of the removal of adult content and certain artists from the training dataset?

    -The removal of adult content and certain artists is significant as it helps improve the quality of generated images, particularly in terms of anatomy, and reduces the necessity for using negative prompts.

  • How does the new Stable Diffusion 2.1 model handle celebrity images?

    -Stable Diffusion 2.1 has improved its handling of celebrity images, enabling the generation of superhero images and addressing previous complaints about the original celebrity pictures.

  • What is the recommended way to support the creator of the Stable Diffusion UI?

    -The recommended way to support the creator of the Stable Diffusion UI is by buying them a coffee or supporting them with GitHub Stars if you are using the notebook extensively.

Outlines

00:00

🚀 Introduction to Stable Diffusion 2.1

The video begins with the host welcoming viewers and introducing the release of Stable Diffusion 2.1 by Stability AI. The host expresses excitement about the update and mentions that it can be accessed using various methods, including diffusers and automatic UI. The video aims to demonstrate how to access the new version and what changes and improvements users can expect. The host also discusses the challenge of reproducibility with the new model, particularly concerning seed values and configurations, and calls for more detailed sharing from Stability AI in future releases. The content then shifts to discussing the improvements made in Stable Diffusion 2.1, such as the removal of adult content and certain artists to address anatomy issues, and the introduction of new features like celebrity and superhero image generation. The host shares a demo image generated using the new model and provides instructions on how to access and use Stable Diffusion 2.1 through a GitHub repository and a user-friendly UI.

05:02

🎨 Exploring Stable Diffusion 2.1's Features

The host proceeds to demonstrate the capabilities of Stable Diffusion 2.1 using a simple prompt to generate an image of a young Chinese girl with studio lighting and bright colors. The discussion touches on the ethical considerations of what the model might consider 'ugly' and the potential for it to create better images. The video showcases the lightweight and quick setup process of the UI, which allows for free use on Google Colab. The host explains the various features available in the UI, including text-to-image, image-to-image, in-painting, and upscaling models. The video also compares the new model's performance with previous versions, particularly in generating images using prompts related to trending on ArtStation. The host encourages viewers to experiment with different steps and seed values to achieve desired results and provides a link to a tutorial for creating close-up portraits. The video concludes with a demonstration of using the UI for generating images with various prompts and adjusting settings like negative prompts to improve image quality.

10:03

📚 Conclusion and Further Exploration

In the final paragraph, the host wraps up the video by emphasizing the improvements in Stable Diffusion 2.1, especially in relation to using keywords like 'training on ArtStation'. The host also appreciates the efforts of kunash, the creator of the lightweight UI for Stable Diffusion, which simplifies the process of getting started with the tool. The video provides information on where to download the ckpt file for those who prefer not to use a UI and how to use the diffusers Library directly. The host expresses hope that the video was helpful and invites viewers to share their experiences and improvements they've found with Stable Diffusion 2.1, particularly in the area of human anatomy. The video ends with an invitation for viewers to join the host in the next video session for more creative prompting.

Mindmap

Keywords

💡Stable Diffusion 2.1

Stable Diffusion 2.1 is an updated version of an AI model developed by Stability AI, which is used for generating images from text prompts. It is significant in the video as it is the main subject being discussed, with the presenter showing how to access and use it. The update aims to improve upon the previous version by addressing issues such as anatomy and content quality.

💡Colab

Colab, short for Google Colaboratory, is a cloud-based platform for machine learning where users can run Jupyter notebooks. In the context of the video, it is used to run a user interface for Stable Diffusion 2.1, allowing the presenter to demonstrate the generation of images without the need for extensive setup.

💡Reproducibility

Reproducibility in the context of AI image generation refers to the ability to recreate the same image using the same prompt and settings. The video discusses the challenge of reproducing images generated by Stable Diffusion, emphasizing the importance of sharing detailed settings and seed values for successful replication.

💡Anatomy

Anatomy, as mentioned in the video, is a term borrowed from biological sciences but applied here to describe the detailed and accurate representation of body structures in generated images. The presenter discusses how Stable Diffusion 2.1 has improved the depiction of human anatomy, which was a criticism of the previous version.

💡Training Data Set

The training data set refers to the collection of data used to teach the AI model how to generate images. The video mentions that Stability AI changed the training data set for Stable Diffusion 2.1 by removing adult content and certain artists, which was done to enhance the quality and accuracy of the generated images.

💡Negative Prompts

Negative prompts are terms or phrases included in the text prompt to guide the AI model to avoid including certain elements in the generated image. The video script discusses the use of negative prompts to refine the output of Stable Diffusion 2.1, such as preventing cartoonish or deformed results.

💡UI (User Interface)

UI, or User Interface, is the part of a computer program that users interact with. In the video, the presenter introduces a lightweight UI for Stable Diffusion 2.1 that allows users to input prompts and generate images more easily. The UI is accessible through a GitHub repository and is designed to be user-friendly.

💡GitHub Repository

A GitHub repository is a location where developers can store their projects and collaborate with others. In the context of the video, the presenter directs viewers to a specific GitHub repository where they can find the Stable Diffusion 2.1 UI and use it on Colab.

💡Seed Value

The seed value is a number used to initialize the random number generator in AI models, ensuring that the same seed will produce the same output. The video emphasizes the importance of sharing the seed value when presenting AI-generated images to facilitate reproducibility.

💡Art Station

Art Station is an online platform where artists showcase their work. The video discusses how the previous version of Stable Diffusion had issues with generating images based on prompts that included 'training on Art Station,' but the new version, Stable Diffusion 2.1, seems to have improved in this regard.

💡Superheroes

Superheroes are a popular theme in the video, where the presenter mentions that Stable Diffusion 2.1 now has the capability to generate images of superheroes. This is one of the new features highlighted in the video, showing the versatility of the AI model in creating different types of content.

Highlights

Stability AI has released Stable Diffusion 2.1, which can be accessed using diffusers.

The release addresses issues with anatomy in previous versions by changing the training dataset.

Adult content and certain artists that resulted in bad anatomy have been removed from the training data.

Stable Diffusion 2.1 is trained on Stable Diffusion 2.0 with additional information.

The new model has improved the use of prompts such as 'trending on ArtStation'.

Celebrity and superhero images have been enabled in Stable Diffusion 2.1.

Reproducibility of images generated by the model has been improved.

A lightweight Stable Diffusion UI GUI is available on GitHub, created by kunash.

The UI allows for easy access to Stable Diffusion 2.1 on Google Colab.

Users can now generate images with prompts and adjust settings such as seed value and guidance scale.

The UI supports text-to-image, image-to-image, in-painting, and upscaling models.

The UI is lightweight and quick to set up, taking about 26-27 seconds to start.

The new version of Stable Diffusion shows promise in generating better quality images.

Users can try Stable Diffusion 2.1 by visiting the provided GitHub repository and using the Colab link.

The model ID can be changed to use Stable Diffusion 2.1 directly from the diffusers library.

The CKPT file for Stable Diffusion 2.1 can be downloaded for use in other UIs.

The video demonstrates the use of the new version with various prompts and settings.

The presenter discusses the ethical considerations of the model's understanding of what is 'ugly'.

The community's feedback on the model's improvements, especially in human anatomy, is encouraged.