AnimateDiff - GIF Animation for A1111 and Google Colab

Olivio Sarikas
24 Jul 202310:20

TLDRThe video tutorial introduces 'AnimateDiff,' a tool for creating GIF animations that can be used with both A1111 and Google Colab. The presenter guides viewers through the installation process for the A1111 extension and the Google Colab version, emphasizing the need for checkpoint files. The video showcases various examples of animations generated with different settings, such as the number of frames, frames per second, and sampling methods. It also explains how to customize prompts and use the tool in Google Colab, including downloading and editing YAML files for personal use. The presenter notes that while the extension can produce impressive results, achieving high-quality output may require further experimentation. The video concludes with a discussion on the efficiency of using Google Colab with a paid plan or credits for faster rendering times.


  • 😀 AnimateDiff is a tool for creating GIF animations that can be used within Automatic1111 or Google Colab for more consistent results.
  • 🔧 The GitHub page for AnimateDiff provides a wealth of information, installation guides, and sample outputs.
  • 📚 There are multiple installation methods available, including a Gradle version, an Automatic1111 web UI extension, and a Google Colab version.
  • 💾 To use AnimateDiff locally, checkpoint files are needed, with versions 1.4 and 1.5 suggested for download and placement in specific Automatic1111 directories.
  • 🖼️ The quality of animations can be adjusted with parameters such as the number of frames, frames per second, and rendering settings like ddim sampling method and resolution.
  • 🎨 The tutorial demonstrates how to enable and configure AnimateDiff within Automatic1111, including setting the number of frames and choosing models.
  • 📸 Examples of rendered outputs are provided, showcasing different settings and their effects on the quality and style of the animations.
  • 🔗 For Google Colab users, a direct link is provided to open Google Colab with AnimateDiff pre-configured, simplifying the setup process.
  • 🛠️ Users can customize their animations by editing YAML configuration files, which control aspects like seed, steps, guidance scale, and prompts.
  • 📁 The process of saving and rendering custom animations in Google Colab is outlined, including how to download the final GIF files.
  • ⏱️ Render times can vary based on the version of Google Colab used, with the free version taking longer compared to paid plans with faster GPU access.

Q & A

  • What is the purpose of AnimateDiff?

    -AnimateDiff is a tool used to create GIF animations, and it can be utilized within Automatic1111 and Google Colab for generating animations with stable diffusion.

  • How can I find more information about AnimateDiff and see examples of its output?

    -You can visit the GitHub page for AnimateDiff, which contains a lot of information, samples of how the animations should look, and different versions for installation.

  • What are the different versions of AnimateDiff mentioned in the script?

    -The script mentions a Gradio version, an Automatic1111 web UI extension, and a Google Colab version of AnimateDiff.

  • How do I install the AnimateDiff extension for Automatic1111?

    -To install the AnimateDiff extension, go to the extensions page, click on 'Available', load from the list, search for 'AnimateDiff', and then click 'Install'. After installation, click 'Installed', 'Apply and Restart', and restart Automatic1111 completely.

  • What additional software do I need to run AnimateDiff on my local computer?

    -To run AnimateDiff locally, you need checkpoint files, specifically mmsd version 1.4 or 1.5, which can be downloaded from the provided link in the video.

  • Where should I place the downloaded checkpoint files for AnimateDiff?

    -The downloaded checkpoint files should be placed in the Automatic1111 folder, then in the extensions folder, followed by the SD web UI animate diff folder, and finally in the models folder.

  • What is the minimum number of frames recommended for good quality in AnimateDiff animations?

    -At least eight frames are recommended for good quality in AnimateDiff animations. Having less than that may result in significantly poorer image quality.

  • What are some of the settings commonly used with AnimateDiff?

    -Common settings include using the ddim sampling method with 25 steps, a resolution of 512 by 512, and a CFG scale of 7.5.

  • How can I access the AnimateDiff extension in Automatic1111?

    -In Automatic1111, AnimateDiff will appear as one of the areas where you can choose from a pop-up for your models, and you need to enable it to make it work.

  • How does the process of creating an animation in Google Colab differ from Automatic1111?

    -In Google Colab, you click on a link to open it, then click on a play icon to install AnimateDiff, which takes a while. After installation, you can set up your animation parameters and start rendering. The rendered GIFs are found in a folder named after the yaml file and timestamp.

  • What is the recommended approach for using Google Colab for rendering AnimateDiff animations?

    -The recommended approach is to use the 'pay as you go' option for 100 computer units, which are good for 90 days and can be used for GPU time rendering.



🎨 'Animating with Stable Diffusion'

This paragraph introduces the video's focus on creating animations using Stable Diffusion, a tool that can be integrated with Automatic1111 or used in Google Colab for better consistency and output. The speaker suggests visiting the GitHub page for more information and examples, such as realistic vision animations. The maximum frame generation is 24, and the audience is guided on how to install the tool using different versions, including a web UI extension and a Google Colab version. The importance of checkpoint files is highlighted, with specific versions (mmsd version 1.4 and 1.5) recommended for download and placement in the Automatic1111 folder structure. The speaker also discusses settings for frame quality, frame rate, and sampling methods, suggesting experimentation for optimal results.


🖥️ 'Using Animated Diff in Google Colab'

The second paragraph delves into the process of using Animated Diff in Google Colab. It explains how to access and use the tool through a provided link, which opens Google Colab and initiates the installation process. The speaker outlines the steps to configure the tool, including setting frame length, width, and height, and discusses the use of YAML files for customizing animation parameters. The paragraph provides guidance on editing and creating YAML files using a node editor, with suggestions for settings like steps, guidance scale, and prompts. It also covers how to save and execute the YAML file in Google Colab, and how to download the resulting animated outputs. The speaker mentions the rendering time differences between the free version of Google Colab and the Pro Plan with GPU support, offering advice on the most cost-effective approach for users.


📺 'Conclusion and Call to Action'

The final paragraph serves as a conclusion and call to action for the video. It invites viewers to subscribe to the channel for more similar content and hints at the presence of an end screen with additional video suggestions. The speaker encourages viewers to like the video if they haven't already, and expresses hope for their return, creating a friendly and engaging conclusion to the tutorial.




AnimateDiff is a tool that allows users to create GIF animations. In the context of the video, it is used to generate animations within the AI platform 'Stable Diffusion' and Google Colab. The script mentions that AnimateDiff has a GitHub page where users can find more information and samples of the animations it can create.


GitHub is a web-based platform for version control and collaboration used by software developers. In the video, the speaker suggests checking out the AnimateDiff GitHub page for more information, installation guides, and examples of the animations it can produce.

💡Stable Diffusion

Stable Diffusion is an AI model used for generating images and animations. The video discusses using AnimateDiff with Stable Diffusion, particularly focusing on creating realistic animations with it. The script also mentions the need for checkpoint files for Stable Diffusion to work with AnimateDiff.

💡Google Colab

Google Colab is a cloud-based platform that allows users to run Jupyter notebooks. The video script highlights that AnimateDiff works more consistently and provides better output when used in Google Colab, as opposed to the AI platform 'Stable Diffusion'.


In the video, the term 'extension' refers to a plugin or add-on for a web application or software. The speaker demonstrates how to install the AnimateDiff extension for 'Stable Diffusion' and mentions that it can be found in the extensions section of the software.

💡Checkpoint Files

Checkpoint files in the context of AI models like Stable Diffusion are used to save the state of training or the current state of a model. The script instructs viewers to download specific versions of checkpoint files for Stable Diffusion to work with AnimateDiff.


Frames refer to the individual images that make up an animation or video. The video discusses setting the number of frames for an animation in AnimateDiff, with the speaker noting that at least eight frames are needed for good quality.

💡FPS (Frames Per Second)

Frames Per Second (FPS) is a measure of how many individual images (frames) are displayed per second in a video or animation. The script explains that users can set the FPS in AnimateDiff to control the playback speed of the animation.

💡DDIM Sampling Method

DDIM stands for 'Denoising Diffusion Implicit', a sampling method used in AI models to generate images. The video script mentions that people often use the DDIM sampling method with AnimateDiff, along with specific settings like 25 steps and a resolution of 512 by 512.

💡CFG Scale

CFG Scale refers to the 'Classifier-Free Guidance' scale, a parameter in AI image generation models that controls the level of detail or 'steering' in the generated image. The video uses a CFG scale of 7.5 as an example setting for AnimateDiff.

💡CLIP Skip

CLIP Skip is a parameter that determines how closely the generated image adheres to the input prompt. The script provides examples of using different CLIP skip values to test their effects on the output animations.

💡YAML File

YAML stands for 'YAML Ain't Markup Language' and is a human-readable data serialization format. The video script instructs viewers on how to create and use YAML files to configure settings for AnimateDiff in Google Colab.


Introduction to AnimateDiff, a tool for creating GIF animations.

AnimateDiff can be used in both Automatic1111 and Google Colab for better output consistency.

The GitHub page for AnimateDiff offers extensive information and sample animations.

Realistic Vision animations can be created with a maximum of 24 frames.

Installation instructions for AnimateDiff are available on the GitHub page.

AnimateDiff can be installed as an extension in Automatic1111.

Checkpoint files are required for local computer use, with versions 1.4 and 1.5 suggested.

Instructions on how to enable and set up AnimateDiff in Automatic1111.

The importance of having at least eight frames for good animation quality.

Settings for frame per second, looping, and model placement in CPU.

Recommended settings for ddim sampling method, steps, resolution, and CFG scale.

Downloading the beta 5 file of the tune model for use in Automatic1111.

Challenges with getting high-quality output in Automatic1111 and the need for experimentation.

Examples of rendered animations using different prompts and settings.

How to use AnimateDiff in Google Colab and the installation process.

Details on rendering multiple commands simultaneously in Google Colab.

Parameters and configurations used in Google Colab for rendering animations.

How to generate and customize your own YAML files for AnimateDiff.

Using a node editor to customize YAML files for specific animation settings.

Instructions on saving and uploading custom YAML files for rendering in Google Colab.

Downloading the rendered GIF animations from Google Colab.

Options for using Google Colab with a free version or a paid subscription for faster rendering.

Recommendation for using pay-as-you-go credits for GPU time in Google Colab.