2024! Stable Diffusion in Colab Notebook for FREE with no disconnects. FREE Midjourney alternative.

marat_ai
6 Feb 202406:36

TLDRDiscover how to use Stable Diffusion for free in Google Colab without a subscription, powerful GPU, or fear of disconnections. The video explains a new method compliant with Google's policies, ensuring longevity and accessibility. It guides viewers through setting up the notebook, choosing between two model types, and generating images with various styles and details. It also discusses the limitations of certain features due to hardware constraints and offers solutions, including downloading higher-resolution images. For advanced features, a paid Patreon version is available, which supports more sophisticated model options and user interfaces.

Takeaways

  • 🌐 The video discusses a method to use Stable Diffusion for free in Google Colab without needing a powerful GPU or paying for a subscription.
  • 🚫 The creator has made several Google Colab notebooks, but most have been banned for violating Google's policies.
  • 🎯 The new notebook created is designed to avoid bans as it does not violate any Google Colab rules.
  • 📝 Users are instructed to open a provided link and select Python 3 and T4 GPU as the runtime type.
  • 🔍 Two model options are presented: 'sdxl' and 'ISD XL with refiner', with the latter offering more detailed image generation but certain restrictions.
  • 🖼️ The 'sdxl' model is recommended for basic usage, and the process for installing and using it is explained in detail.
  • 🛠️ The interface of the notebook is simple but slightly counterintuitive, with guidance provided on how to enter prompts and generate images.
  • ⏱️ Image generation takes approximately 10 seconds, but the initial output is not in full resolution.
  • 📸 Full resolution images can be accessed and downloaded from a specific tab in the notebook.
  • 🔗 The use of a 'Lora' model is demonstrated, with a focus on its application in image generation.
  • 💡 The creator mentions plans to improve the notebook and offers more advanced features through a Patreon subscription.

Q & A

  • What is the purpose of the video discussed in the transcript?

    -The video is designed to guide viewers on how to use Stable Diffusion for free on Google Colab notebooks without needing a powerful GPU, a paid subscription, or experiencing disconnects.

  • Why have many of the Google Colab notebooks created by the speaker been banned?

    -The majority of the Google Colab notebooks created by the speaker have been banned because they were violating Google's usage rules.

  • What is 'invoke AI' mentioned in the transcript?

    -'invoke AI' is one of the notebooks mentioned by the speaker that is still operational, although there is an expectation that it may eventually be banned as well.

  • What are the two model options available for use in the notebook as described in the video?

    -The two model options available in the notebook are 'SDXL' and 'SDXL with refiner.'

  • Why doesn't the SDXL model with refiner work with lower model tiers?

    -The SDXL model with refiner doesn't work with lower models due to real restrictions, likely related to computational or hardware limitations.

  • What advantage does using the SDXL model with refiner provide?

    -Using the SDXL model with refiner provides more detailed outputs in the generated images, which is crucial for high-quality image generation.

  • What should a user do if they want to generate an image using the notebook?

    -To generate an image, the user needs to enter a prompt, select the number of images, style, and advanced settings like seed, resolution, and steps, and then press the 'generate' button in the specified cell.

  • How can a user download full-resolution images generated in the notebook?

    -Users can download full-resolution images by navigating to the 'output images' tab and clicking the download button next to the generated images.

  • What is the 'Lura' model mentioned in the transcript, and how is it used in the notebook?

    -The 'Lura' model appears to be a specific functionality or enhancement that can be applied to images in the notebook. Users can download and apply it by entering a link to the model, loading it, and then running the cell to apply it to generated images.

  • What additional features does the speaker mention are available to Patreon subscribers?

    -For Patreon subscribers, the speaker has created a different version of the notebook that allows the selection of various other models like 'delate realistic vision' or custom models, potentially offering more advanced functionalities.

Outlines

00:00

📚 Introduction to Free SA Diffusion in Google Colab

The speaker introduces a method to utilize SA (Stability-Aesthetics) diffusion for free in a Google Colab notebook. They mention previous attempts and the challenges faced due to Google's policy restrictions, leading to the creation of a new notebook that complies with Google's rules. The speaker provides a step-by-step guide on setting up the notebook, including choosing the appropriate runtime type, selecting the model (either SDXL or SD XL with refiner), and understanding the limitations of the refiner option. They also highlight the importance of the refiner for image detail and quality, while noting that the XL without refiner is sufficient for basic needs. The interface of the notebook is described as simple but slightly counterintuitive, and the speaker explains the process of entering prompts, selecting styles, and generating images. The output is noted to be in a lower resolution initially, with full-resolution images available upon navigating to a specific tab.

05:00

🔍 Exploring Additional Features and Future Improvements

The speaker discusses the limitations of the current notebook setup, particularly the inability to use ISD XL with refiner in conjunction with lower models due to restrictions. They express intent to fix this issue and mention the existence of a more advanced notebook version available to Patreon subscribers. This version offers additional model options, such as realistic Vision or custom models, and potential future features like image-to-image tabs and control options. The speaker acknowledges the challenges in implementing these advanced features in an understandable way due to the current interface's limitations. They conclude by encouraging viewers to subscribe to their Patreon and channel for access to various stable notebooks and to look forward to future updates and improvements.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is a term used in the context of AI and machine learning to describe a model that generates images from textual descriptions. In the video, it is the primary technology being discussed, which allows users to create images without the need for powerful hardware or paid subscriptions. The video outlines a method to use this technology for free in a Google Colab notebook, which is a cloud-based platform for coding and running programs.

💡Colab Notebook

A Colab Notebook is a cloud-based Jupyter notebook that allows users to write and execute Python code, and it is particularly useful for machine learning and data analysis tasks. Google Colab provides free access to GPU resources, making it possible to run computationally intensive programs without the need for personal high-performance computing devices. In the video, the speaker guides the audience on how to utilize Colab Notebooks to access Stable Diffusion without any costs.

💡Midjourney

Midjourney is referenced in the video as an alternative to Stable Diffusion. It is likely an AI-based image generation platform or tool that may require payment or have other access restrictions. The video positions the method it's presenting as a free alternative to such services, emphasizing the cost-saving benefits for users who wish to generate images without incurring any expenses.

💡Disconnects

In the context of the video, 'disconnects' refers to the interruptions or loss of connection that users might experience while using online services or platforms. The speaker assures the audience that the method they will discuss does not result in disconnects, implying a smooth and uninterrupted experience when using the Stable Diffusion model in a Google Colab Notebook.

💡GPU

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. In the video, the mention of not requiring a powerful GPU indicates that the method being discussed allows users to utilize AI image generation services without the need for high-end, graphically-intensive hardware.

💡Invoke AI

Invoke AI, as mentioned in the video, seems to be a specific implementation or instance of AI services that the speaker has created in the form of Google Colab notebooks. It is suggested that this service has not been banned and is currently operational, unlike other similar attempts that have been restricted due to violations of Google's policies.

💡Stable Diffusion Models

The term 'Stable Diffusion Models' refers to the different versions or configurations of the Stable Diffusion AI model that can be used for image generation. The video mentions two specific models: 'sdxl' and 'SD XL with refiner.' The distinction between these models lies in their capabilities and the level of detail they can produce in the generated images. The 'refiner' appears to enhance the detail and quality of the images, but it is not compatible with lower models due to certain limitations.

💡Refiner

In the context of the video, a 'refiner' seems to be a component or feature of the Stable Diffusion model that enhances the quality and detail of the generated images. It is suggested that the refiner improves the final output, making the images more detailed and visually appealing. However, its use is contingent on the model being utilized, as lower models may not support it.

💡Prompt

A 'prompt' in the context of AI image generation refers to the textual input or description that guides the AI in creating an image. It is a critical element in the process as it sets the theme, style, or content of the image that the AI will produce. The video script describes how users can enter prompts to generate images with specific characteristics or themes, such as 'ugly' or 'image count' to specify the number of images produced.

💡Styles

In the context of the video, 'styles' refer to the different artistic or visual themes that can be applied to the images generated by the Stable Diffusion model. These styles can range from 'anime' to 'photography' or 'comic books,' and they influence the aesthetic and visual elements of the resulting images. The selection of styles allows users to customize the output to match their preferences or the requirements of their projects.

💡Lora

In the video, 'Lora' seems to refer to a specific model or feature within the Stable Diffusion technology that can be applied to the generated images. It is mentioned in the context of adding a logo or a specific visual element to the images. The term 'Lora' might be a specific term or name used within the community of users for this particular functionality or model.

💡Patreon

Patreon is a platform that allows creators to offer exclusive content or services to their subscribers, typically in exchange for a monthly fee. In the context of the video, Patreon is mentioned as a platform where the speaker provides additional resources, such as another version of the notebook with more advanced features, available exclusively to their patrons. This suggests that the speaker has a tiered system of content distribution, with free resources available to the public and more sophisticated tools accessible to supporting subscribers.

Highlights

Using Stable Diffusion for free in Google Colab Notebook without powerful GPU or pay subscription.

Avoiding disconnects by not violating Google Colab rules.

Creation of numerous Google Colab notebooks for the past 8 months.

Invoke AI is currently the only working notebook that hasn't been banned.

Introduction of a simple notebook for basic Stable Diffusion usage.

Selecting the proper notebook type: Python 3 and T4 GPU.

Two model options: SDXL and SD XL with Refiner.

SD XL with Refiner provides more detailed images but has model restrictions.

SD XL without Refiner is sufficient for basic usage in most cases.

Installation of all required components and the SDXL model takes approximately 5 minutes.

Simple interface with intuitive controls for prompt, style, and generation settings.

Generating images by pressing the 'Generate' button, with results appearing in about 10 seconds.

Access to full-resolution images by navigating to the 'Output Images' tab.

Applying the Lora model for specific image styles.

Downloading and using the Lora model for image generation.

SD XL does not currently work with Lora or custom models.

An alternative version of the notebook with advanced features is available for Patreon subscribers.

The current notebook is ideal for basic usage, with more sophisticated options available through Patreon.

The presenter encourages subscribing to their channel for access to various stable notebooks.

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