The strongest AI painting open source tool FLUX, local deployment and installation tutorials

The previously released Stable Diffusion 3 model has been criticized for being over-audited, resulting in a "regression" in the ability to generate human structures.

Now an excellent pinto has appeared, the Black Forest Laboratory'sFLUXFLUX was released to rave reviews, and was named the "strongest open source literate graph model".

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

Compared to header closed-source tools such as Midjourney and DALLE, FLUX's performance is still respectable.

FLUX currently supportsComfyUIGraphical User Interface, described nextLocal deploymentThe methodology:

Step 1: Install the latest version of ComfyUI

1. Go to the following URL: https://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing

2. Click Direct link to download to download a zip file of about 1.5G.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

3. Extract the zip package to your designated hard disk.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

4. Enter the installed directory and run run_nvidia_gpu.bat, then the system will automatically download the necessary files.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

5, after which will automatically pop up a web page similar to this, indicating that the installation was successful.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

Note: This background window should be kept open, otherwise ComfyUI will not work properly.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

Step 2: Download the FLUX model

1. Go to FLUX's hug face page: https://huggingface.co/black-forest-labs/FLUX.1-dev/tree/main and click the Files button:

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

2. In the file list, download the master model file and the VAE self-encoder:
flux1-dev.sft: 23.8 GB, put this file in the ComfyUI/models/unet/ directory
ae.safetensors: 335 MB, put this file in the ComfyUI/models/vae/ directory

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

3. Enter the ComfyUI Hugging Face page: https://huggingface.co/comfyanonymous/flux_text_encoders/tree/main

4. In the file list, download the CLIP pre-training model:
t5xxl_fp16.safetensors: 9.79 GB
t5xxl_fp8_e4m3fn.safetensors: 4.89 GB
clip_l.safetensors: 246 MB
All of the above files are placed in the ComfyUI/models/clip/ directory, with at least one of the 9GB and 4GB files downloaded.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

5. Go to the following URL: https://openart.ai/workflows/maitruclam/comfyui-workflow-for-flux-simple/iuRdGnfzmTbOOzONIiVV and click the Download button on the right to download the workflow.

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

6. Drag the workflow file onto the ComfyUI page to get the result shown below:

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

7. Make sure you have selected the correct model and encoder (refer to the picture below) and then you can start painting!

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

It should be noted that FLUX has high hardware requirements. During the test, it took up to nearly 30G of RAM:

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

FLUX is also slow in generating images, even with a 4090 graphics card with default settings, it takes more than 20 seconds to generate a 1024x1024 image:

The strongest AI painting open source tool FLUX, local deployment and installation tutorials

But considering the increased odds of a one-time success, slow seems acceptable?

The article covers the URL:

FLUX's Github page:
https://github.com/black-forest-labs/flux

ComfyUI's Github page:
https://github.com/comfyanonymous/ComfyUI

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