Google Colab Stable Diffusion | Stable Diffusion Ai Tutorial

Planet Ai
22 Oct 202304:22

TLDRThis video tutorial offers a straightforward guide on utilizing stable diffusion without the need for high-end computing resources. It introduces a free Google Colab notebook that enables users to run stable diffusion and install various models. The process involves changing the runtime to T4 GPU, executing cells to install the desired models, and using the Invoke AI platform for image generation. The video also provides tips on handling potential errors and introduces the presenter's WhatsApp channel for additional content.


  • 🌐 The video introduces a method to use stable diffusion for free without needing a high-end CPU.
  • 📚 A free Google Colab notebook is shared as a resource for utilizing stable diffusion.
  • 🔍 Attention is necessary when following the video to avoid ads and ensure proper setup.
  • 💡 Change the runtime to T4 GPU in Google Colab for optimal performance.
  • 🛠 The initial setup involves running code cells that may take 3 to 4 minutes to execute.
  • 🔗 A link is provided to access a variety of stable diffusion models within the Colab notebook.
  • 🎨 Users can select and install their desired models, including versions like stable Vision realistic version 5.
  • 🔄 The process may show errors, but they are part of the process and can be resolved by rerunning the cell.
  • 🖼️ Once the setup is complete, users can generate images using prompts and select options like number of images and steps.
  • 🔄 An upscaling feature is available for enhancing the quality of the generated images.
  • 📌 The video creator also invites viewers to join their WhatsApp community for more updates and resources.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about using stable diffusion for free without the need for a high-end CPU, by utilizing a Google Colab notebook.

  • What is the first step in setting up the Google Colab notebook?

    -The first step is to go to the 'Runtime' menu, select 'Change runtime type', and choose 'T4 GPU' as the runtime instead of the default 'CPU'.

  • How long does it typically take for the first cell to execute?

    -It usually takes around 3 to 4 minutes for the first cell to execute.

  • What is the purpose of the blue link in the video?

    -The blue link allows users to view all the stable def Fusion models that can be installed within the Google Colab notebook.

  • How can you install a different version of the stable diffusion model?

    -To install a different version, you can replace the default model selection with the desired version's code, for example, by changing 'stab Vision realistic version 5' to 'true' for version 5 of stab diffusion.

  • What is the function of the 'Invoke AI' link in the video?

    -The 'Invoke AI' link provides access to the stable diffusion feature within the notebook, where users can enter prompts and generate images based on those prompts.

  • How does one add a new model to the notebook?

    -To add a new model, users can go to the 'Model Manager', select 'Import Model', and paste the link address of the desired model that they have copied from the source, such as CVI.

  • What is the purpose of the 'upscale' button in the video?

    -The 'upscale' button is used to enhance the resolution of the generated images by selecting an upscaling model, such as 'real s4x plus'.

  • How can users download the generated images?

    -Users can download the generated images by clicking on the image and selecting the 'Download image' option.

  • What additional features are available for image generation that were not shown in the video?

    -Additional features include seed values selection, the number of images, the number of steps, and the canvas option, which are not shown in the video due to length constraints.

  • How can viewers stay updated with the latest content from the video creator?

    -Viewers can join the creator's WhatsApp Community through the link provided in the video description to receive updates on the latest content.



💻 Introduction to Using Stable Diffusion on Google Colab

The paragraph introduces the concept of utilizing stable diffusion technology without the need for high-end computing resources. It presents a free Google Colab notebook as a solution for individuals who lack access to powerful CPUs. The speaker guides the audience through the process of using the notebook, emphasizing the importance of following the steps carefully to avoid issues. The video promises a simple yet effective method to execute code and install desired models within the Colab environment.



💡Stable Diffusion

Stable Diffusion is an AI model that generates images from textual descriptions. It is a type of deep learning algorithm that has been trained on a large dataset of images and text. In the context of the video, it is the primary tool being discussed, which allows users to create realistic images without the need for high-end computing resources.

💡Google Colab

Google Colab is a free cloud-based platform that allows users to write and execute Python code in a collaborative environment. It is particularly popular among data scientists and machine learning enthusiasts for its ease of use and the ability to run code on powerful GPUs without the need for expensive hardware. In the video, Google Colab is the platform where the Stable Diffusion model is being utilized.


T4 GPU refers to a specific type of graphics processing unit designed by NVIDIA. It is a high-performance GPU that is optimized for AI and machine learning tasks. In the context of the video, selecting the T4 GPU in Google Colab allows users to leverage the GPU's processing power for running the Stable Diffusion model without needing to invest in a high-end computer.

💡Code Execution

Code execution is the process of running a set of programming instructions to produce a result. In the video, code execution is essential as it involves running cells in the Google Colab notebook to set up the environment and install the Stable Diffusion model. The video emphasizes the importance of following the steps carefully to ensure successful code execution.

💡Model Installation

Model installation involves the process of adding or setting up a specific AI model within a software environment. In the video, model installation is a key step in preparing the Google Colab notebook to use Stable Diffusion, allowing users to select and add different versions or types of models to generate images based on their preferences.

💡Invoke AI

Invoke AI refers to the act of calling upon or utilizing an artificial intelligence system to perform a specific task. In the video, Invoke AI is the interface within the Google Colab notebook that allows users to interact with the Stable Diffusion model, input prompts, and generate images.

💡Negative Prompt

A negative prompt is a feature in AI image generation models that allows users to specify what elements should not be included in the generated image. This helps in refining the output and ensuring that the final image aligns more closely with the user's vision.

💡Model Manager

The Model Manager is a tool or interface within AI platforms that allows users to manage, add, or remove different models. In the context of the video, the Model Manager is used to import and add new Stable Diffusion models to the Google Colab notebook, providing users with the ability to customize their AI image generation experience.

💡Text to Image

Text to Image is a feature of AI models like Stable Diffusion that converts textual descriptions into visual images. This functionality is based on the model's ability to understand and interpret language to create corresponding visual content. In the video, Text to Image is the primary method by which users generate images using Stable Diffusion within Google Colab.


Upscaling refers to the process of increasing the resolution or size of an image without losing quality. In the context of the video, upscaling is an additional feature that allows users to enhance the quality of the images generated by the Stable Diffusion model, providing them with more options for using the final output.


Community, in this context, refers to a group of individuals who share common interests and interact with each other regularly, often through online platforms. The video creator mentions a WhatsApp Community as a place where they share the latest news and cool stuff, indicating a community of like-minded individuals interested in technology and AI.


A free Google Colab notebook is shared for using Stable Diffusion without the need for a high-end CPU.

The video provides a method to utilize Stable Diffusion for those without advanced computer specifications.

Instructions are given on how to change the runtime to T4 GPU in Google Colab for using the notebook.

The process of executing the code in the first cell of the notebook is explained, which may take 3 to 4 minutes.

A link is provided to view all the Stable Diffusion models that can be installed within the Google Colab notebook.

The default model selected is Stable Vision realistic version 5, but other versions can be chosen by replacing the code.

The video demonstrates how to install desired models from CVI (Cutting-Edge AI) into the Google Colab notebook.

The Invoke AI platform is introduced, which allows users to enter prompts and generate images using Stable Diffusion.

Options for negative prompts, number of images, and number of steps are available in Invoke AI for customization.

Model manager feature in Invoke AI is showcased for adding new models by pasting the model link.

A step-by-step guide on how to add a new model from CVI and use it in the text-to-image section is provided.

An example prompt is given to generate a hyper-realistic image of a beautiful lady with freckles in a coffee shop.

The option to upscale the generated image using different upscaling models is discussed.

The video encourages viewers to join the creator's WhatsApp channel for sharing the latest cool stuff.

The final image generated is showcased, demonstrating the quality and realism of the Stable Diffusion model.

The video concludes by highlighting the ease of using Stable Diffusion in Google Colab and encourages viewers to like the video.