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TLDRBlack Forest Labs introduces Flux, a groundbreaking 12 billion parameter AI model surpassing all previous versions in image generation quality and prompt adherence. Flux, available in two versions, the standard and a faster, slightly lower quality 'Shel' variant, can be run locally or online for minimal cost. The video provides installation instructions for both manual setup and using a Maring installer, and offers tips for optimizing GPU usage for the best performance. Flux's uncensored capabilities and potential training limitations are also discussed.
Takeaways
- 😲 A new AI model called 'flux' by Black Forest Labs has been released, which outperforms previous models in image generation quality and prompt following.
- 🌟 Flux is a 12 billion parameter model capable of generating highly realistic images, including correct hands and anime styles.
- 🔍 The company behind flux, Black Forest Labs, is a small team of 15 people, 14 of whom are from Stability AI.
- 💻 Users can run the flux model locally on their computers or online for a minimal cost.
- 🛠️ There are two installation methods for flux: an automated installer for Patreon supporters and a manual installation process.
- 🔧 The automated installer simplifies the process by handling the installation of confy UI and the flux models.
- 📁 Manual installation requires downloading several files and placing them into specific folders within the confy UI directory.
- 🚀 Flux offers different versions of the model, including a 'flux chel' version that generates images faster but with slightly reduced quality.
- 🎛️ Optimal performance is achieved by configuring the GPU settings correctly, such as preferring no cism fallback for models with ample VRAM.
- 📉 For users with less VRAM, using the fp8 version of the model and adjusting settings like weight D type to 'fp16' can improve performance.
- 🤖 Flux's ability to understand and generate images from complex prompts is impressive, though it is not completely uncensored and cannot generate explicit content.
- 🔮 The future of flux's trainability is uncertain, as training a 12 billion parameter model may require significant computational resources beyond consumer-grade GPUs.
Q & A
What is the name of the new AI model released by Black Forest Labs?
-The new AI model released by Black Forest Labs is called 'flux'.
How many parameters does the flux model have?
-The flux model has a huge 12 billion parameters.
What are the unique features of the flux model compared to previous models?
-The flux model can generate beautiful images with correct hands, almost perfect text photo realism, anime, and follows the prompt even better than stable diffusion 3 or any other model released up until now.
How many people are in the team at Black Forest Labs?
-Black Forest Labs is a small team of 15 people.
How many team members of Black Forest Labs come from Stability AI?
-14 members of the Black Forest Labs team come from Stability AI.
What are the two ways to install the flux model as mentioned in the script?
-The two ways to install the flux model are by using the Maring installer for Patreon supporters, and the manual way which involves downloading and extracting files, and placing them into precise folders.
What is the difference between the 'fast low vram install' and the 'unoptimized normal model'?
-The 'fast low vram install' is recommended for users with less than 12 GB of vram, while the 'unoptimized normal model' is for users with more than 12 GB of vram, which allows for faster image generation at the cost of higher vram usage.
What is the recommended model to use according to the script?
-The script recommends using the fp8 version of the flux model, as it is optimized and requires less vram to run.
What is the name of the super fast version of the flux model?
-The super fast version of the flux model is called 'flux schel'.
How much time does it take for the flux schel model to generate an image?
-The flux schel model can generate an image in around 2 seconds, which is significantly faster than the normal flux model.
What is the main concern regarding the future of the flux model mentioned in the script?
-The main concern is whether the flux model can be trained and the computational power required for training such a large model, which might not be feasible on consumer-grade GPUs.
Outlines
🚀 Introduction to Flux AI Model
The video introduces a groundbreaking AI model named Flux, developed by Black Forest Labs, a relatively unknown company with a team primarily from Stability AI. Flux is a 12 billion parameter model that excels at generating high-quality images with correct hands and text-photo realism, surpassing previous models like Stable Diffusion 3. The video promises a tutorial on installing Flux and discusses potential issues yet to be confirmed.
🛠️ Installing Flux: Methods and Tips
The script outlines two methods for installing the Flux AI model. The first method involves using an installer for patrons, which simplifies the process by automatically downloading models and setting up the software. The second method is a manual installation, which requires downloading specific files and placing them in the correct folders. The video provides detailed steps for both methods, including the use of the fast low VRAM install and the choice between different versions of the Flux model for optimal performance.
🎨 Optimizing GPU Settings for Flux
The paragraph discusses how to optimize GPU settings for generating images with Flux. It covers the importance of adjusting the CUDA compute fallback policy to maximize VRAM usage and the selection of appropriate data types to balance speed and image quality. The video also introduces the Flux Shel model, a faster version that compromises slightly on quality for rapid image generation. Additionally, it shows how to use a cloud-based GPU service for those without powerful local hardware.
🌐 Remote GPU Usage and Model Capabilities
This section guides viewers on deploying a GPU pod remotely to run Flux using a service like Runpod. It explains the process of setting up the environment, including disk space allocation and template selection. The video also highlights the model's impressive capabilities, such as understanding complex prompts and generating detailed images, including anime styles. However, it raises concerns about the model's censoring level and the feasibility of training such a large model due to computational demands.
🔮 Future Considerations and Conclusion
The final paragraph addresses the uncertainty surrounding the model's trainability and the potential need for significant computational resources, suggesting that training Flux might not be feasible on consumer-grade GPUs. Despite these concerns, the video celebrates the model's current capabilities and encourages viewers to try it out. It also thanks patrons for their support and invites viewers to subscribe and engage with the content.
Mindmap
Keywords
💡AI Model
💡Black Forest Labs
💡Parameters
💡Text-to-Image Generation
💡Flux Model
💡VRAM
💡Config UI
💡FP8
💡Runpod
💡Censorship
💡Training
Highlights
Introduction of a new AI model called 'flux' by Black Forest Labs.
Flux is a 12 billion parameters model that outperforms previous models like Stable Diffusion 3.
Black Forest Labs is a new company with a team mostly from Stability AI.
Flux can generate images with correct hands, text, photorealism, and anime styles.
Flux models can be run locally on a computer or online for a few cents an hour.
Installation of flux involves using the Maring installer or manual installation.
Instructions for installing flux using the confy UI manager Auto installer.
Explanation of choosing the 'fast low vram install' option during installation.
Downloading the flux model files for installation.
Optimized 'flux chel' model introduced for faster image generation.
Flux model's ability to generate images with less VRAM usage through FP8 optimization.
NVIDIA settings adjustments for optimal image generation with flux.
Comparison of flux's image generation time and VRAM usage with Stable Diffusion 3.
Demonstration of flux's image generation with different models and settings.
Flux's uncensored nature compared to Stable Diffusion 3.
Potential issues with flux's trainability and the need for significant computational power.
How to rent a GPU for running flux on platforms like runpod.
Instructions for setting up flux on runpod with pre-prepared files for Patreon supporters.
Final thoughts on flux's capabilities and the community's potential to enhance it further.