QWEN IMAGE 2.1 LORA TRAINING!
Hey everyone! I've created a 1-click installer for QWEN IMAGE 2.1 EDIT LORA TRAINING! This model is already an incredible image editor, but with your own custom LoRAs, you can do so much more with it, and of course the results are amazing!
You can check out the video right here: https://youtu.be/_YF8GC6Qd2I
The installer, of course, automates the entire installation process!
I've also attached a ZIP archive containing both the control and main dataset folders used for the PS1 training, along with four PS1 LoRA checkpoints saved at 250, 500, 750, and 1,000 steps. You can try the LoRAs yourself, compare the different versions, and look through the training pairs to see exactly how the dataset was made so that you can follow along with the video!
Important: I deliberately trained this PS1 LoRA to allow a certain amount of variation in the results, as explained in the video (it was for my own project) so keep that in mind when testing the LoRAs or using the dataset as a reference for your own training.
LINK TO THE XY PLOT LORA WORKFLOW: https://www.patreon.com/aitrepreneur/posts/172067666
LOCAL INSTALL!!! RECOMMENDED TO HAVE AT LEAST 10GB (or 8GB/64RAM ) OF VRAM FOR THE Qwen image 2.1 Edit LORA TRAINING! if it's an issue, definitely use the Runpod installer instead, as recommended in the video!
Local install:
Requisites:
– CUDA 12.8 (RTX-50) OR CUDA 12.6 (RTX-40/30/20/GTX)
– Git, Python 3.10 64-bit, Node 18/20 LTS
1. Download the AI-TOOLKIT_AUTO_INSTALL.bat and place it in a folder WITHOUT any spaces in the path!!!
2. Run the bat file and select either option 1 or 2 depending on your GPU
3. Wait for the install to finish
4. ???
5. Profit 😎
Use then one of the launcher once you have closed the ui and you want to restart it.
RUNPOD:
1. Create an account if you haven't already: Runpod
2. Click on Pod (on the left side) then click deploy
3. Choose a GPU (4090-5090), and chose the pytorch 2.8.0 then edit the template and choose 100GB for the volume disk, then under expose ports, edit:
8888 into 8888, 8675. Then go into environment variables below, click add and then type:
AI_TOOLKIT_AUTH on the left then type a password on the right
then scroll then and deploy.
4. Go to my pods, wait for everything to finish and then click "connect", then "Connect to HTTP SERVICE port 8888"
5. Then drag and drop the AI-TOOLKIT_AUTO_INSTALL-RUNPOD_FAST.sh file on the left side of the UI then click on the "Terminal" icon on the right side on the UI
6. Copy and paste this line then press enter:
bash "AI-TOOLKIT_AUTO_INSTALL-RUNPOD_FAST.sh"
7. Wait for everything to be installed
8. Go back to the port 8675 and click on it to launch the webui then enter your password you created previously
As always, supporting me on Patreon allows me to keep creating helpful resources like this for the community. Thank you for your support - now go have some fun😉!