How to Run Flux Image Models In ComfyUI with Low VRAM

The Local Lab
15 Aug 202411:42

TLDRThis video tutorial guides viewers on how to run Flux image models in ComfyUI, even with low VRAM. It introduces Flux models by Black Forest Labs and the use of quantized versions to reduce VRAM usage. The video provides a step-by-step installation process for ComfyUI, necessary extensions, and the Python library. It also offers a workflow for using Flux models, with tips for managing different models and settings to optimize image generation, making AI art creation accessible on modest hardware.

Takeaways

  • 🌐 The video introduces Flux, a family of AI image generation models developed by Black Forest Labs, which includes Schnell, Dev, and Flux Pro models.
  • 🎨 Flux has gained popularity for its high-quality AI-generated art, with images often shared on social media platforms like Twitter and Reddit.
  • 💻 Flux models are known to be resource-intensive, requiring significant VRAM, but the introduction of quantized and F4 versions makes them accessible on systems with 4 to 10 GB of VRAM.
  • 🚀 The NF4 versions of Flux models offer faster performance and lower system requirements, making AI art generation more accessible.
  • 🛠️ ComfyUI is presented as a user-friendly graphical user interface (GUI) for AI image generation, rivaling other popular tools like Stable Diffusion.
  • 🔧 The video provides a step-by-step guide to installing ComfyUI and setting up a workflow for using the quantized Flux NF4 models.
  • 📚 The tutorial includes instructions for downloading and installing necessary components like the ComfyUI manager and the Bits and Bites NF4 extension.
  • 🔗 Links to GitHub repositories and model files are provided in the video description for easy access and setup.
  • 🖼️ The video demonstrates how to use ComfyUI to generate AI art with Flux models, including how to switch between different models and adjust settings for desired results.
  • 💡 The presenter encourages viewers to experiment with settings and share their workflows or tips for improving AI art generation.
  • 🔄 The video also offers a pro tip on how to keep ComfyUI and custom nodes updated for optimal performance and access to the latest features.

Q & A

  • What is Flux and how has it impacted the AI art scene?

    -Flux is a family of AI image generation models developed by Black Forest Labs. It has taken the AI art scene by storm, creating jaw-dropping images that have flooded social media platforms like Twitter and Reddit.

  • What are the different models within the Flux family?

    -The Flux family consists of Schnell, the Speedster for quick tests; the Dev model, an all-rounder balancing speed and quality; and Flux Pro, the powerhouse for professionals seeking peak performance.

  • Why are the unquantized versions of Flux models considered VRAM intensive?

    -The unquantized versions of Flux models require a significant amount of VRAM, with 20 GB or more needed for the full experience, making them demanding on system resources.

  • What is the significance of the low bit acceleration method introduced by the creator of Stable Diffusion?

    -The low bit acceleration method allows for the creation of quantized and F4 versions of Flux models that are less demanding on VRAM, enabling users with modest 4 to 10 GB of VRAM to experience Flux's capabilities.

  • What is ComfyUI and how does it relate to Flux models?

    -ComfyUI is a popular GUI for AI image generation that supports running Flux models. It has gained popularity for its flexibility and power, making it a go-to platform for artists working with Flux.

  • How can users install ComfyUI on their system?

    -Users can install ComfyUI by downloading the portable standalone build for Windows from the releases page, then extracting the contents of the 7z file to their desired location on their hard drive.

  • What additional software is required to run Flux models in ComfyUI?

    -To run Flux models in ComfyUI, users need to install Git to manage GitHub repositories, and possibly additional extensions and a Python library as detailed in the script.

  • How do users get the Flux NF4 models into ComfyUI?

    -Users download the NF4 Flux models from the provided links on GitHub, then place the model files into the checkpoints folder within the ComfyUI directory.

  • What is the workflow in ComfyUI and why is it necessary?

    -The workflow is a set of instructions that tell ComfyUI how to use the Flux models. It's necessary for configuring the AI image generation process and can be loaded into ComfyUI for easy use.

  • How long does it typically take for Flux models to generate images on ComfyUI?

    -The time it takes for Flux models to generate images can vary, with the Dev model taking 5 to 10 minutes and the Schnell model around 2 minutes on a 6 GB RTX 4050 GPU.

  • What is the ComfyUI manager and how does it help users?

    -The ComfyUI manager is a tool that simplifies the process of managing and updating ComfyUI, including installing updates and adding new models and nodes as they become available.

Outlines

00:00

🖼️ Introduction to AI Image Generation with Flux Models

The video begins with an introduction to AI image generation, specifically focusing on Flux models developed by Black Forest Labs. Flux models are a family of AI models designed for different purposes, including Schnell for quick tests, the Dev model for a balance of speed and quality, and Flux Pro for peak performance. The video aims to demystify how Flux works and how viewers can use it without needing high-end hardware. It mentions the availability of quantized and F4 versions of Flux models, which are less demanding on system resources and can run on modest 4 to 10 GB VRAM setups. The video also introduces Comfy UI, a popular GUI for AI image generation, and provides a simple method for installing it along with a pre-made workflow for the new quantized Flux NF4 models.

05:00

🛠️ Setting Up Comfy UI and Installing Flux Models

The second paragraph delves into the technical setup process for using Flux models with Comfy UI. It starts with downloading and installing Comfy UI on a Windows system, guiding viewers to download a portable version and extract it to their desired location. The video then instructs viewers to install 'git' to manage GitHub repositories, which are necessary for running Flux models. The setup continues with cloning the Comfy UI manager and the necessary extensions for managing and running Flux models. The video also covers the installation of a Python library required for the NF4 extension. Finally, it guides viewers on how to download and install the Flux NF4 models from GitHub and set up the workflow for generating AI images.

10:02

🚀 Generating AI Art with Flux Models

The final paragraph demonstrates how to generate AI art using the Flux models within Comfy UI. It explains the process of launching Comfy UI and loading the pre-made workflow, selecting the desired Flux model, and initiating the image generation process. The video highlights the differences between the Dev and Schnell models, with the former producing higher quality images and the latter offering faster results. It also provides tips on improving generation speeds and experimenting with settings and resolutions. The video concludes with advice on keeping Comfy UI and custom nodes updated and encourages viewers to share their workflows and tips in the comments section.

Mindmap

Keywords

💡Flux models

Flux models refer to a family of AI image generation models developed by Black Forest Labs. These models are known for their ability to produce high-quality images and have gained significant attention in the AI art community. In the video, the speaker discusses different models within the Flux family, each designed for specific use cases such as quick tests, balanced performance, or professional use, highlighting their impact on the AI art scene.

💡VRAM

VRAM, or Video Random Access Memory, is a type of memory used by graphics processing units (GPUs) to store image data. The video mentions that Flux models, particularly the unquantized versions, can be demanding on VRAM, requiring 20 GB or more for optimal performance. This is a critical consideration for users looking to run these models, as it may limit accessibility for those with lower-end hardware.

💡Bit quantization

Bit quantization is a technique used to reduce the memory and computational requirements of AI models by reducing the precision of the numbers they use. The video discusses how quantized versions of Flux models have been made available, allowing users with less VRAM (4 to 10 GB) to still experience the benefits of Flux models. This is significant as it makes advanced AI image generation more accessible to a broader range of users.

💡ComfyUI

ComfyUI is a graphical user interface (GUI) for AI image generation that has gained popularity for its flexibility and power. It is mentioned as the 'playground' or 'digital canvas' where users can utilize Flux models. The video provides a guide on how to set up ComfyUI with specific workflows designed for the new quantized Flux models, making it easier for users to get started with AI art creation.

💡GitHub

GitHub is a web-based platform for version control and collaboration used by developers to store and manage code. In the context of the video, GitHub is where users can find and download the ComfyUI manager, extensions for running Flux models, and the models themselves. The video instructs viewers on how to use GitHub to access these necessary components for AI image generation.

💡Stable Diffusion

Stable Diffusion is another AI model for image generation, mentioned in the video as a comparison to Flux models. The speaker discusses how Flux has made an impact similar to that of Stable Diffusion, but with its own unique capabilities and strengths. This comparison helps to position Flux within the broader landscape of AI image generation tools.

💡NF4 versions

NF4 versions refer to the quantized and optimized versions of the Flux models that are designed to be more efficient in terms of memory usage. The video explains that these versions are not only lighter on the system but also faster, making them ideal for users with modest hardware who still want to create high-quality AI-generated art.

💡Workflow

In the context of ComfyUI, a workflow is a set of instructions or a sequence of steps that the software follows to complete a task, such as generating an image with a specific model. The video provides a pre-made workflow for the quantized Flux NF4 models, which simplifies the process for users by removing the need to configure settings manually.

💡Checkpoints

Checkpoints in AI model training refer to the saved states of the model at various points during the training process. In the video, checkpoints are used to load the Flux models into ComfyUI. The speaker guides users on where to place the downloaded model files within the ComfyUI directory structure to ensure they can be accessed and used correctly.

💡Resolution

Resolution in digital imaging refers to the number of pixels used to form the image and determines the level of detail that can be seen. The video mentions that users can experiment with different resolutions when generating images with Flux models, with higher resolutions resulting in more detailed images but longer generation times.

Highlights

Introduction to AI image generation with Flux models.

Flux models are a family of AI models developed by Black Forest Labs.

Schnell, the speed-focused model, is ideal for quick tests and experiments.

The dev model offers a balance between speed and image quality.

Flux Pro is the high-performance model for professionals.

Unquantized Flux models require over 20 GB of VRAM.

Introduction of quantized and F4 versions of Flux models for lower VRAM usage.

ComfyUI is a popular GUI for AI image generation with over 46,000 stars on GitHub.

A step-by-step guide to install ComfyUI and run Flux models.

Downloading the ComfyUI Windows portable Nvidia 7z file.

Using 7z file archiver to extract ComfyUI files.

Installing G to manage GitHub repositories.

Adding custom nodes to ComfyUI for managing and running Flux models.

Installing the ComfyUI manager for easier management.

Downloading and installing the bits and bites NF4 extension for Flux models.

Installing the bits and bytes Python library for NF4 extension.

Downloading the NF4 Flux models from the GitHub page.

Placing the downloaded models in the checkpoints folder.

Loading the pre-made workflow for Flux models in ComfyUI.

Using the dev model for higher quality image generation.

Using the Schnell model for faster image generation at the cost of detail.

Tips for improving generation speeds and experimenting with settings.

Using the ComfyUI manager to keep the AI Art Studio up to date.

Encouragement to explore, experiment, and create stunning AI art.

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