what’s the hype around flux, the new image generation model?
Eric Hal Schwartz
2024-08-10
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<p>A new AI image generator named Flux.1 has burst onto the scene and is rapidly accruing kudos for its high-end results and the fact that it's an open-source model. Flux was built by Black Forest Labs, whose founders were previously at Stability AI, the creator of the popular Stable Diffusion line of AI image models. </p><p>Some are calling the Flux stable of models the successor to Stable Diffusion and possibly a major game-changer for accessible, high-quality generative AI tools.</p><p>There are three versions of Flux.1: Pro, Dev, and Schnell, in decreasing order of size. The Pro version is designed for commercial use, with companies already incorporating it to offer generative AI image services to their subscribers. The Dev and Schnell versions are optimized for different levels of performance and speed.</p><p>What sets Flux apart from Midjourney, Stable Diffusion, and many of its competitors? Most notably, the two smaller models can run on reasonably good hardware, such as high-performance laptops. This makes it more accessible to a broader range of users, including hobbyists, developers, and small businesses who may not have the resources to invest in more expensive, proprietary tools. It also means you don't have to rely on internet access or cloud storage to run Flux. And, while Midjourney has been praised for its ability to create highly detailed and visually appealing images, Flux claims to offer some distinct advantages, particularly in rendering human figures. Black Forest Labs is now working on adding a text-to-video model to its portfolio.</p><p>"Deeply rooted in the generative AI research community, our mission is to develop and advance state-of-the-art generative deep learning models for media such as images and videos, and to push the boundaries of creativity, efficiency and diversity. We believe that generative AI will be a fundamental building block of all future technologies,"  Black Forest Labs explained in its <a href="https://blackforestlabs.ai/announcing-black-forest-labs/">blog</a>. "By making our models available to a wide audience, we want to bring its benefits to everyone, educate the public and enhance trust in the safety of these models. We are determined to build the industry standard for generative media."</p><div><blockquote><p>We are excited to announce the launch of Black Forest Labs. Our mission is to develop and advance state-of-the-art generative deep learning models for media and to push the boundaries of creativity, efficiency and diversity. pic.twitter.com/ilcWvJgmsX<a href="https://twitter.com/bfl_ml/status/1819003686011449788">August 1, 2024</a></p></blockquote></div><h2>How to get and use Flux</h2><p>For those interested in exploring Flux, there are several ways to access and use the model. If your computer is good enough, you can download and run Flux.1 locally. Plus, Flux is an open-source model and compatible with multi-model platforms, which expands its availability significantly. </p><p>AI image platform NightCafe has already integrated the Flux.1 model, allowing users to compare its outputs directly with those from other models like Ideogram and Stable Diffusion 3. </p><div><section><p>Sign up for breaking news, reviews, opinion, top tech deals, and more.</p></section></div><p>Similarly, Poe offers a <a href="https://www.techradar.com/tag/chatbot">chatbot</a>-style interface for generating images using Flux.1. For those a little more technical, you can also access Flux.1 through Hugging Face and other hubs of open-source AI models.</p><h3></h3><ul><li><a href="https://www.techradar.com/computing/artificial-intelligence/google-gemini-will-soon-let-you-edit-those-ai-generated-images-to-fix-the-3-eyed-dogs-and-impossible-buildings">Google Gemini will soon let you edit those AI-generated images to fix the 3-eyed dogs and impossible buildings</a></li><li><a href="https://www.techradar.com/computing/artificial-intelligence/amds-new-ai-image-generator-for-windows-will-make-images-right-on-your-pc-forget-the-cloud">AMD's new AI image generator for Windows will make images right on your PC – forget the cloud</a></li><li><a href="https://www.techradar.com/news/i-tried-googles-text-to-image-ai-and-was-shocked-by-the-results">I tried Google's text-to-image AI, and I was shocked by the results</a></li></ul>
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<div><p>Eric Hal Schwartz is a freelance writer for TechRadar with more than 15 years of experience covering the intersection of the world and technology. For the last five years, he served as head writer for Voicebot.ai and was on the leading edge of reporting on generative AI and large language models. He's since become an expert on the products of generative AI models, such as OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini, and every other synthetic media tool. His experience runs the gamut of media, including print, digital, broadcast, and live events. Now, he's continuing to tell the stories people want and need to hear about the rapidly evolving AI space and its impact on their lives. Eric is based in New York City.</p></div>
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 1. Computing
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 3. Artificial Intelligence

 A major new Midjourney rival has landed – here’s how to try the open-source Flux

 News
 By Eric Hal Schwartz
 published 10 August 2024

 AI image generation made easy

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 (Image credit: Flux)

 A new AI image generator named Flux.1 has burst onto the scene and is rapidly accruing kudos for its high-end results and the fact that it's an open-source model. Flux was built by Black Forest Labs, whose founders were previously at Stability AI, the creator of the popular Stable Diffusion line of AI image models.

 Some are calling the Flux stable of models the successor to Stable Diffusion and possibly a major game-changer for accessible, high-quality generative AI tools.

 There are three versions of Flux.1: Pro, Dev, and Schnell, in decreasing order of size. The Pro version is designed for commercial use, with companies already incorporating it to offer generative AI image services to their subscribers. The Dev and Schnell versions are optimized for different levels of performance and speed.

 What sets Flux apart from Midjourney, Stable Diffusion, and many of its competitors? Most notably, the two smaller models can run on reasonably good hardware, such as high-performance laptops. This makes it more accessible to a broader range of users, including hobbyists, developers, and small businesses who may not have the resources to invest in more expensive, proprietary tools. It also means you don't have to rely on internet access or cloud storage to run Flux. And, while Midjourney has been praised for its ability to create highly detailed and visually appealing images, Flux claims to offer some distinct advantages, particularly in rendering human figures. Black Forest Labs is now working on adding a text-to-video model to its portfolio.

 "Deeply rooted in the generative AI research community, our mission is to develop and advance state-of-the-art generative deep learning models for media such as images and videos, and to push the boundaries of creativity, efficiency and diversity. We believe that generative AI will be a fundamental building block of all future technologies," Black Forest Labs explained in its blog. "By making our models available to a wide audience, we want to bring its benefits to everyone, educate the public and enhance trust in the safety of these models. We are determined to build the industry standard for generative media."

 We are excited to announce the launch of Black Forest Labs. Our mission is to develop and advance state-of-the-art generative deep learning models for media and to push the boundaries of creativity, efficiency and diversity. pic.twitter.com/ilcWvJgmsXAugust 1, 2024

 How to get and use Flux

 For those interested in exploring Flux, there are several ways to access and use the model. If your computer is good enough, you can download and run Flux.1 locally. Plus, Flux is an open-source model and compatible with multi-model platforms, which expands its availability significantly.

 AI image platform NightCafe has already integrated the Flux.1 model, allowing users to compare its outputs directly with those from other models like Ideogram and Stable Diffusion 3.

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 Similarly, Poe offers a chatbot-style interface for generating images using Flux.1. For those a little more technical, you can also access Flux.1 through Hugging Face and other hubs of open-source AI models.

 You might also like

 * Google Gemini will soon let you edit those AI-generated images to fix the 3-eyed dogs and impossible buildings
 * AMD's new AI image generator for Windows will make images right on your PC – forget the cloud
 * I tried Google's text-to-image AI, and I was shocked by the results

 Eric Hal Schwartz
 Contributor

 Eric Hal Schwartz is a freelance writer for TechRadar with more than 15 years of experience covering the intersection of the world and technology. For the last five years, he served as head writer for Voicebot.ai and was on the leading edge of reporting on generative AI and large language models. He's since become an expert on the products of generative AI models, such as OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini, and every other synthetic media tool. His experience runs the gamut of media, including print, digital, broadcast, and live events. Now, he's continuing to tell the stories people want and need to hear about the rapidly evolving AI space and its impact on their lives. Eric is based in New York City.

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A major new Midjourney rival has landed – here’s how to try the open-source Flux
https://www.techradar.com/computing/artificial-intelligence/a-major-new-midjourney-rival-has-landed-heres-how-to-try-the-open-source-flux
None
2024-08-14T00:00:00Z
<div><article><h2><a href="#Flux:-The-Julia-Machine-Learning-Library">Flux: The Julia Machine Learning Library</a><a></a><a href="#Flux:-The-Julia-Machine-Learning-Library"></a></h2><p>Flux is a library for machine learning. It comes "batteries-included" with many useful tools built in, but also lets you use the full power of the Julia language where you need it. We follow a few key principles:</p><ul><li><strong>Doing the obvious thing</strong>. Flux has relatively few explicit APIs. Instead, writing down the mathematical form will work – and be fast.</li><li><strong>Extensible by default</strong>. Flux is written to be highly flexible while being performant. Extending Flux is as simple as using your own code as part of the model you want - it is all <a href="https://github.com/FluxML/Flux.jl/tree/master/src">high-level Julia code</a>.</li><li><strong>Play nicely with others</strong>. Flux works well with unrelated Julia libraries from <a href="https://github.com/JuliaImages/Images.jl">images</a> to <a href="https://github.com/SciML/DifferentialEquations.jl">differential equation solvers</a>, rather than duplicating them.</li></ul><h3><a href="#Installation">Installation</a><a></a><a href="#Installation"></a></h3><p>Download <a href="https://julialang.org/downloads/">Julia 1.9</a> or later, preferably the current stable release. You can add Flux using Julia's package manager, by typing <code>] add Flux</code> in the Julia prompt.  For Nvidia GPU support, you will also need to install the <code>CUDA</code> and the <code>cuDNN</code> packages. For AMD GPU support, install the <code>AMDGPU</code> package. For acceleration on Apple Silicon, install the <code>Metal</code> package.</p><h3><a href="#Learning-Flux">Learning Flux</a><a></a><a href="#Learning-Flux"></a></h3><p>The <strong><a href="https://fluxml.ai/Flux.jl/stable/guide/models/quickstart/#man-quickstart">quick start</a></strong> page trains a simple neural network.</p><p>This rest of the <strong>guide</strong> provides a from-scratch introduction to Flux's take on models and how they work, starting with <a href="https://fluxml.ai/Flux.jl/stable/guide/models/overview/#man-overview">fitting a line</a>. Once you understand these docs, congratulations, you also understand <a href="https://github.com/FluxML/Flux.jl">Flux's source code</a>, which is intended to be concise, legible and a good reference for more advanced concepts.</p><p>There are some <strong>tutorials</strong> about building particular models. The <strong><a href="https://github.com/FluxML/model-zoo/">model zoo</a></strong> has starting points for many other common ones. And finally, the <strong><a href="https://fluxml.ai/Flux.jl/stable/ecosystem/">ecosystem page</a></strong> lists packages which define Flux models.</p><p>The <strong>reference</strong> section includes, beside Flux's own functions, those of some companion packages: <a href="https://github.com/FluxML/Zygote.jl">Zygote.jl</a> (automatic differentiation), <a href="https://github.com/FluxML/Optimisers.jl">Optimisers.jl</a> (training) and others.</p><p>Everyone is welcome to join our community on the <a href="https://discourse.julialang.org/">Julia discourse forum</a>, or the <a href="https://discourse.julialang.org/t/announcing-a-julia-slack/4866">slack chat</a> (channel #machine-learning). If you have questions or issues we'll try to help you out.</p><p>If you're interested in hacking on Flux, the <a href="https://github.com/FluxML/Flux.jl">source code</a> is open and easy to understand – it's all just the same Julia code you work with normally. You might be interested in our <a href="https://github.com/FluxML/Flux.jl/labels/good%20first%20issue">intro issues</a> to get started, or our <a href="https://github.com/FluxML/Flux.jl/blob/master/CONTRIBUTING.md">contributing guide</a>.</p></article></div>||||I||||  Search docs (Ctrl + /)
    * Welcome
    * Guide
        + Quick Start
        + Fitting a Line
        + Gradients and Layers
        + Custom Layers
        + Training
        + Recurrence
        + GPU Support
        + Saving & Loading
        + Performance Tips
    * Ecosystem
    * Reference
        + Built-in Layers
        + Activation Functions
        + Weight Initialisation
        + Loss Functions
        + Training API
        + Optimisation Rules
        + Shape Inference
        + Flat vs. Nested
        + Callback Helpers
        + Gradients – Zygote.jl
        + Batching Data – MLUtils.jl
        + OneHotArrays.jl
        + Low-level Operations – NNlib.jl
        + Nested Structures – Functors.jl
    * Tutorials
        + Linear Regression
        + Logistic Regression
        + Model Zoo
      Version
      * Welcome
      * Welcome
       GitHub 

    Flux: The Julia Machine Learning Library

    Flux is a library for machine learning. It comes "batteries-included" with many useful tools built in, but also lets you use the full power of the Julia language where you need it. We follow a few key principles:

      * Doing the obvious thing. Flux has relatively few explicit APIs. Instead, writing down the mathematical form will work – and be fast.
      * Extensible by default. Flux is written to be highly flexible while being performant. Extending Flux is as simple as using your own code as part of the model you want - it is all high-level Julia code.
      * Play nicely with others. Flux works well with unrelated Julia libraries from images to differential equation solvers, rather than duplicating them.

    Installation

    Download Julia 1.9 or later, preferably the current stable release. You can add Flux using Julia's package manager, by typing ] add Flux in the Julia prompt. For Nvidia GPU support, you will also need to install the CUDA and the cuDNN packages. For AMD GPU support, install the AMDGPU package. For acceleration on Apple Silicon, install the Metal package.

    Learning Flux

    The quick start page trains a simple neural network.

    This rest of the guide provides a from-scratch introduction to Flux's take on models and how they work, starting with fitting a line. Once you understand these docs, congratulations, you also understand Flux's source code, which is intended to be concise, legible and a good reference for more advanced concepts.

    There are some tutorials about building particular models. The model zoo has starting points for many other common ones. And finally, the ecosystem page lists packages which define Flux models.

    The reference section includes, beside Flux's own functions, those of some companion packages: Zygote.jl (automatic differentiation), Optimisers.jl (training) and others.

    Community

    Everyone is welcome to join our community on the Julia discourse forum, or the slack chat (channel #machine-learning). If you have questions or issues we'll try to help you out.

    If you're interested in hacking on Flux, the source code is open and easy to understand – it's all just the same Julia code you work with normally. You might be interested in our intro issues to get started, or our contributing guide.

    Quick Start »

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Welcome · Flux
https://fluxml.ai/Flux.jl/stable/