Cách cài đặt Stable Diffusion full gọn nhẹ dễ dàng bằng Google Colab

Phan Đông Giang
10 Sept 202308:23

TLDRThe video script introduces a method to utilize Google Colab for free, enabling users with low-spec machines to access powerful computing resources. The host, Phan, demonstrates how to set up and connect to Google Colab, highlighting the benefits of using it, such as the ability to access up to 12 GB of RAM and 72 GB of disk space. He also explains the process of installing Stable Diffusion on Google Colab without the need for extensive PC resources. The video ends with a teaser on how to generate ideas using AI and promises a detailed guide in the next video.


  • 🌟 The video introduces a method to use Stable Diffusion, a powerful AI tool, for free without needing a high-end machine.
  • 💻 Google Colab is highlighted as a platform that allows users to utilize resources provided by Google to run Stable Diffusion.
  • 📈 The script mentions that most laptops and computers might struggle with the high system requirements of Stable Diffusion.
  • 🔍 To check if a machine can run Stable Diffusion, it is advised to check the GPU specifications, preferably with at least 4 or 6 GB of VRAM.
  • 🔧 The video provides a step-by-step guide on how to connect to Google Colab and utilize its resources to run Stable Diffusion on a regular PC.
  • 🚀 Google Colab offers extended resources, such as 12 GB of RAM and 72 GB of disk space, enhancing the user experience.
  • 📌 The video emphasizes the ease of using Stable Diffusion on Google Colab, as it comes preloaded with various models and checkpoints.
  • 🎉 The process of setting up and using Stable Diffusion on Google Colab is presented as simple and accessible to all users.
  • 🔗 The video mentions two links that appear once Stable Diffusion is successfully installed on Google Colab, indicating readiness for use.
  • 🛠 The script suggests that users can generate ideas and content using Stable Diffusion, with the creator demonstrating how to input an ID into the tool.
  • 📚 The video concludes by mentioning that more detailed instructions and examples will be provided in subsequent videos.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about how to use Google Colab, a free and lightweight alternative to powerful machines, for machine learning and other computational tasks.

  • Why is Google Colab considered a good option for those with less powerful machines?

    -Google Colab is considered a good option because it allows users to utilize Google's resources without the need for a high-specification machine, making it accessible for those with less powerful laptops or computers.

  • What are the system requirements to use the traditional version of stablevision?

    -The traditional version of stablevision typically requires a machine with a high-end graphics card, at least 4 or 6 GB of VRAM, and a powerful CPU and RAM to run smoothly.

  • How can one check if their machine is suitable for running stablevision?

    -To check if a machine is suitable, one can go to the Device Manager, navigate to the GPU section, and check the specifications of the graphics card to ensure it meets the minimum VRAM requirements.

  • What happens when you connect to Google Colab?

    -Upon connecting to Google Colab, users are provided with access to Google's resources, which can significantly enhance the computing power available to them, allowing for the use of machine learning models and other demanding tasks.

  • What is the advantage of using Google Colab over installing stablevision on a personal computer?

    -The advantage of using Google Colab is that it does not require users to install numerous extensions on their personal computers, and it comes preloaded with many machine learning models and libraries, making the setup and usage process much simpler.

  • How long does it typically take for Google Colab to set up and be ready for use?

    -It usually takes around 5 to 10 minutes for Google Colab to set up and be ready for use, although this may vary depending on the machine's specifications and internet connection speed.

  • What does the video suggest about the availability of pre-trained models in Google Colab?

    -The video suggests that there are many pre-trained models available in Google Colab, which users can easily load and use for their projects without the need to train them from scratch.

  • How can users generate new ideas or concepts using stablevision?

    -Users can utilize the pre-trained models in stablevision to generate new ideas or concepts by inputting specific prompts or IDs, which the model will then use to create outputs that match the user's requirements.

  • What additional resources does the video creator offer to help users with stablevision?

    -The video creator offers additional resources such as a list of pre-trained models and tutorials on their agricultural product channel, which users can refer to for guidance and inspiration.

  • What is the next step for users who have successfully connected to Google Colab?

    -Once users have successfully connected to Google Colab, they can start exploring the available machine learning models, load pre-trained checkpoints, and begin working on their projects using the extended resources provided by Google.



💻 Utilizing Google Colab for Free Machine Learning

This paragraph discusses how users can take advantage of Google Colab to run machine learning models without the need for a high-performance computer. The speaker introduces the concept of using Google Colab, a free service that provides access to GPU resources, which can be particularly beneficial for those with less powerful machines. The instructions include checking the GPU capabilities through the device manager and highlight the ease of connecting to Google Colab. The speaker emphasizes the availability of various pre-trained models and the convenience of using Google Drive for storing and accessing these models. The summary concludes with a mention of the time it takes for the setup process and the appearance of confirmation links, indicating successful installation of the machine learning environment on Google Colab.


🚀 Enhancing Creative Ideas with AI on Google Colab

The second paragraph focuses on the creative potential of using AI tools available on Google Colab for generating ideas. The speaker suggests that by utilizing pre-trained models on Google Colab, users can generate innovative concepts and ideas, such as IDs or other creative tasks. The paragraph details the process of selecting and using various Chrome samples to generate requests for AI models. It also introduces the concept of using a curated list of Chrome models for inspiration and ends with a promise to provide more detailed guidance in a future video. The speaker encourages viewers to look forward to the next video for more comprehensive instructions and insights into leveraging AI for creative purposes.



💡Google Classroom

Google Classroom is an online platform developed by Google for schools that aims to simplify creating, distributing, and grading assignments paperlessly. In the context of the video, it is used as a means to access powerful computing resources provided by Google, allowing users to utilize high-end applications that might not run on their personal computers due to hardware limitations.

💡Stable Vision

Stable Vision likely refers to a technology or software that requires significant computational power to operate. The term might be a mispronunciation or a specific application not clearly defined in the script. However, it is implied that it is a resource-intensive tool that can now be used on less powerful machines through Google Classroom.


A laptop is a portable personal computer with a compact design, typically featuring a touchscreen and a built-in keyboard. In the video, laptops are mentioned as devices that might struggle to run resource-intensive applications like 'stable vision', but can still access these applications through Google Classroom.


Configuration refers to the arrangement of components or settings within a system. In the context of the video, it relates to the hardware specifications required to run certain software or applications. The speaker mentions that to use 'stable vision', a user's PC must have a graphics card with at least 4 or 6 'virant' (possibly a mispronunciation of 'gigabytes' of RAM').

💡Graphics Card

A graphics card is a component in a computer system that renders images, pictures, and videos to the display. It is essential for running applications that require intensive graphical processing. In the video, the graphics card is emphasized as a critical component for running 'stable vision', with a minimum requirement of 4 or 6 'virant' (likely gigabytes) of RAM.

💡Google Drive

Google Drive is a cloud storage service offered by Google that allows users to store, share, and collaborate on files and documents. In the video, it is mentioned as a necessary service to connect and store data when setting up 'stable vision' on Google Classroom.


In the context of machine learning and software applications, a checkpoint is a point at which the internal state of a process is saved so that it can be resumed at a later time. The script mentions downloading checkpoints, which are likely pre-trained models or states of a system that can be used to continue or start a specific operation.


The term 'free' refers to something that is available without cost or payment. In the video, the emphasis is on the accessibility of 'stable vision' and the resources of Google Classroom without any financial burden on the user, highlighting the benefits of using these platforms for individuals with limited resources.


PC stands for Personal Computer, which is a multi-purpose electronic computer for individual use. In the context of the video, PCs are discussed in relation to their hardware limitations and how Google Classroom can help overcome these limitations to run resource-intensive applications.


Extensions are additional software components that enhance or extend the functionality of a platform or application. In the video, the mention of not needing to install many extensions likely refers to the convenience of using Google Classroom, where many features are already integrated and do not require extra installations.


A demo, short for demonstration, is a presentation or trial that showcases the features and capabilities of a product or service. In the video, the speaker mentions doing a demo to show what 'stable vision' looks like when used on Google Classroom, indicating an intention to provide a practical example of its use.


Utilizing Google Colab for free and without the need for a high-performance machine.

The video demonstrates how to install and use Stable Diffusion on devices with low computing power.

Most laptops and computers are difficult to use with Stable Diffusion due to high configuration requirements.

Google Colab allows the use of Google's resources, making it possible to use Stable Diffusion on ordinary machines.

To use Stable Diffusion on a PC, the machine must have a graphics card with at least 4 or 6 gigabytes of VRAM.

Accessing the GPU information through the Device Manager to check if the machine meets the requirements.

Google Colab provides up to 12 GB of RAM and 72 GB of disk space, enhancing the capabilities of low-spec machines.

The process of connecting to Google Colab and utilizing its resources is straightforward and requires a Google account and Chrome browser.

Google Colab allows users to load and use various models and checkpoints without any additional setup.

The video provides a step-by-step guide on how to connect to Google Drive and utilize the available resources.

Once connected, users can wait for the system to allocate resources, typically taking 5 to 10 minutes.

The video emphasizes the ease of using Stable Diffusion on Google Colab without the need to install numerous extensions on a PC.

The presenter shares plans to provide a detailed guide on using the various features and parameters in future videos.

The video demonstrates the potential of generating ideas using Stable Diffusion on Google Colab.

The presenter mentions the use of Chrome models for generating creative ideas and IDs for Stable Diffusion.

The video showcases a collection of Chrome models and encourages viewers to explore and use them for inspiration.

The presenter plans to create a follow-up video detailing the use of check-point models and their applications.