Flux.1 Schnell and Pro - New AI Image Model like Midjourney

Fahd Mirza
1 Aug 202413:16

TLDRDiscover Flux.1, a new AI image model reminiscent of Midjourney, featuring a 12 billion parameter open-source model that harnesses rectified flow Transformers for high-quality image generation. Explore its three versions: the open-source Chanel, the non-commercial Dev, and the API-only Pro. Learn how to install and use Flux.1 locally or via API for stunning image outputs, and stay tuned for their upcoming text-to-video model. Experience the magic of AI-generated art with Flux.1.

Takeaways

  • 😀 Flux.1 is a new AI image model reminiscent of Midjourney, offering text-to-image and image-to-image capabilities.
  • 🔍 Flux.1 is an open-source model with 12 billion parameters, making it compatible with most mid to high-level GPUs.
  • 🌟 The model utilizes rectified flow Transformer technology to generate high-quality images from text descriptions.
  • 📘 Flux.1 comes in three versions: Chanel, Dev, and Pro, each with different licensing and usage restrictions.
  • 🔑 Chanel is open-source under the Apache 2 license, suitable for local development and personal use.
  • 🚫 Flux Dev is a non-commercial license model, distilled from Flux Pro, and is more efficient than standard models of the same size.
  • 💼 Flux Pro is available only through an API and offers state-of-the-art image generation with top-tier visual quality and diversity.
  • 🛠️ The video provides a tutorial on how to install and run Flux.1 Chanel on a local system, including setting up a Python environment and installing prerequisites.
  • 🎨 Viewers are shown examples of images generated by Flux.1, demonstrating the model's capabilities in creating vivid and detailed images.
  • 🔗 The video mentions partnerships with M Compute for GPU sponsorship and provides a discount code for GPU rentals.
  • 📈 Flux.1 models are based on a hybrid architecture, incorporating improvements such as rotary positional embeddings and parallel attention layers for enhanced performance and hardware efficiency.
  • 🎉 An upcoming text-to-video model is teased, which will require a high VRAM GPU, indicating the ongoing development and advancement in AI image generation technology.

Q & A

  • What is the name of the new AI image model introduced in the video?

    -The new AI image model introduced in the video is called 'Flux.1'.

  • Is the Flux.1 model open-sourced?

    -Yes, the Flux.1 model is open-sourced, allowing it to be run on most mid to high-level GPUs.

  • What is special about the rectified flow Transformer mentioned in the video?

    -The rectified flow Transformer is capable of generating high-quality images from text descriptions.

  • How many flavors of the Flux model are available according to the video?

    -There are three flavors of the Flux model available: Flux.1 Chanel, Flux.1 Dev, and Flux.1 Pro.

  • What license does the Flux.1 Chanel model operate under?

    -The Flux.1 Chanel model operates under the Apache 2 License.

  • What is the significance of the 12 billion parameters in the Flux.1 model?

    -The 12 billion parameters indicate the model's size and complexity, suggesting it can generate highly detailed and diverse images.

  • What is the minimum GPU VRAM requirement to run the Flux.1 Pro model locally?

    -The minimum GPU VRAM requirement to run the Flux.1 Pro model locally is at least 80 GB.

  • How can one access the Flux.1 Pro model if they wish to use it?

    -The Flux.1 Pro model can be accessed through an API provided by Fall and a few other providers, including Replicate.

  • What is the cost for running the Flux.1 Pro model via the API?

    -The cost for running the Flux.1 Pro model via the API is approximately 0.5 cents per megapixel.

  • What upcoming feature from the Flux models is mentioned in the video?

    -The upcoming feature mentioned in the video is a text-to-video model.

  • How can one get started with generating images using the Flux.1 Chanel model locally?

    -To get started with generating images locally using the Flux.1 Chanel model, one needs to clone the repo, install the prerequisites, and run the Streamlit demo from the root of the repo.

Outlines

00:00

🚀 Introduction to Fall's New Open-Source Model

The video begins with an introduction to a newly released model called 'Chel' from Fall, which is reminiscent of the popular 'Mid Journey' model. Chel is an open-source, 12 billion parameter model capable of generating high-quality images from text descriptions using a rectified flow Transformer. The video will guide viewers through the installation of Chel on their local systems and demonstrate image generation. Three versions of the model are mentioned: an open-source version under Apache 2 License, a non-commercial 'flux Dev' version, and a commercial 'flux Pro' version accessible via API. The video also acknowledges M Compute for sponsoring the GPU used in the demonstration and provides a discount code for viewers interested in renting GPUs.

05:00

🛠️ Setting Up and Testing the Chel Model

The script continues with a step-by-step guide on setting up the Chel model locally, including creating a Python 3.10 environment and installing prerequisites like torch and Transformers. The repo for flux, provided by Black Forest Lab, is cloned to facilitate the setup process. After installing the prerequisites, the model is launched using a streamlit demo, which also downloads the necessary models. The video discusses the limitations of the presenter's GPU and the model's size, noting that a GPU with at least 80 GB of VRAM is recommended for running the model. The script also provides an overview of the different flux models, emphasizing their hybrid architecture and improvements over previous diffusion models.

10:02

🎨 Exploring Image Generation with Chel

The final paragraph showcases the capabilities of the Chel model by generating images from text prompts. The presenter attempts to run the model locally but encounters issues due to GPU limitations. Instead, the video demonstrates using the Chel model through the Fall platform's API, which allows for image generation at a cost of $0.05 per megapixel. The presenter shares their experience with the API, generating images with vivid details and high definition, and highlights the affordability and accessibility of generating images with the Chel model. The video concludes with an invitation for viewers to explore the Chel model further and to share their thoughts on the content.

Mindmap

Keywords

💡AI Image Model

An AI Image Model refers to a type of artificial intelligence system designed to generate or manipulate images based on input data. In the context of the video, it discusses a new model called 'Flux.1' which is similar to 'Midjourney' and is capable of creating high-quality images from text descriptions. The model is a significant development in the field of AI, as it represents advancements in image generation technology.

💡Midjourney

Midjourney is likely a reference to an existing AI image generation model that has gained popularity. The video suggests that the new 'Flux.1' model will be reminiscent of 'Midjourney' in terms of functionality and quality, indicating that it is a significant comparison point for understanding the capabilities of the new model.

💡Open-sourced

Open-sourced refers to software or models that are publicly accessible and can be modified by anyone. The 'Flux.1' model is described as open-sourced, meaning it can be run on various GPUs and is freely available for use, modification, and distribution, which is a key aspect of its accessibility and community engagement.

💡12 billion parameter model

This term refers to the size and complexity of the AI model, indicating that it has 12 billion parameters that it uses to learn and generate images. A larger number of parameters generally allows for more detailed and nuanced image generation, making the model more capable but also requiring more computational resources.

💡Rectified Flow Transformer

Rectified Flow Transformer is a type of neural network architecture that is capable of generating high-quality images from text descriptions. The video mentions that 'Flux.1' uses this technology, which suggests an advanced method of image synthesis that may offer improved results over traditional approaches.

💡Flux Dev

Flux Dev is one of the flavors or versions of the 'Flux' model mentioned in the video. It is described as having a non-commercial license, implying that it is intended for development and personal use rather than commercial applications, which is an important distinction for potential users to consider.

💡Flux Pro

Flux Pro is another version of the 'Flux' model, which is only available through an API and is intended for commercial use. The video suggests that it offers state-of-the-art performance and image generation capabilities, making it a premium option for businesses and professionals.

💡Hybrid architecture

Hybrid architecture in the context of AI models refers to a combination of different types of neural network components to achieve improved performance. The 'Flux' models are said to be based on a hybrid architecture, which likely contributes to their advanced capabilities in image generation.

💡Parallel diffusion Transformer blocks

Parallel diffusion Transformer blocks are a component of the AI model's architecture that allows for efficient and high-quality image generation. The video mentions that the 'Flux' models have been scaled to a large parameter size and incorporate this technology, indicating a sophisticated approach to AI image synthesis.

💡Rotary positional embeddings

Rotary positional embeddings are a technique used in neural networks to effectively encode the position of elements in the input data. The video suggests that the 'Flux' models use this method to improve model performance, which is an important aspect of their advanced image generation capabilities.

💡Parallel attention layers

Parallel attention layers are a feature of the AI model that allow for the simultaneous processing of different parts of the input data. This can enhance the efficiency and effectiveness of the model, as mentioned in the video, by improving hardware efficiency and model performance.

Highlights

Introduction of a new AI image model, Flux.1, reminiscent of Midjourney.

Flux.1 is an open-source, 12 billion parameter model that can be run on most mid to high-level GPUs.

The model utilizes rectified flow Transformer for high-quality image generation from text descriptions.

Three versions of Flux.1 are available: Chanel, Flux Dev, and Flux Pro, each with different licensing and usage restrictions.

Flux Pro is available only through API and offers state-of-the-art image generation performance.

Flux Dev is a distilled model for non-commercial applications, offering efficiency and quality similar to Flux Pro.

Chanel version is designed for local development and personal use, available under the Apache 2 license.

Installation process includes setting up a Python environment and installing prerequisites like torch and Transformers.

A step-by-step guide to cloning the Flux.1 repo and installing prerequisites from the provided repository.

Launching the model through a streamlit demo, which also downloads the necessary model files.

The model's requirements for GPU VRAM, noting that at least 80 GB is recommended for optimal performance.

Overview of the hybrid architecture of Flux.1, including multimodal and parallel diffusion Transformer blocks.

Mention of upcoming text-to-video model from Flux.1, requiring a high VRAM GPU for operation.

Demonstration of generating images using the API, showcasing the vividness and quality of the output.

Cost analysis of using the Flux.1 API, with pricing per megapixel and the number of runs possible with $1.

Comparison of the user experience between Flux.1 and Midjourney, emphasizing similarities and unique features.

Final thoughts on the potential of Flux.1, encouraging viewers to try the model and share their experiences.

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