Dead Simple Step-by-Step Tutorial for Training FLUX LoRA (Low VRAM Support: 12GB/16GB/20GB)
Added 2025-01-07 12:18:45 +0000 UTCWith the powerful and intuitive FluxGym software, training specialized Flux LoRAs is now easier than ever, taking your image generation to the next level. You don't need to be an expert—FluxGym’s streamlined interface makes advanced model customization accessible, even with limited VRAM. Whether you're working with 12GB, 16GB, or 20GB, FluxGym has you covered.
In this step-by-step tutorial, we cover
🔥 Manual Installation: Get FluxGym up and running with ease!
✨ Setting Up Your First LoRA: Start creating personalized, one-of-a-kind models.
🎨 Using Your LoRA in Image Generation Software: Seamlessly bring your creations to life in your favorite tools.
Why FluxGym?
💻 Low VRAM Support: Works effortlessly with 12GB, 16GB, or 20GB of VRAM.
🖱️ User-Friendly Interface: Enjoy a sleek Gradio UI forked from AI-Toolkit, made for simplicity.
⚙️ Advanced Features: Unlock the full power of Kohya’s sd-scripts via the hidden Advanced tab (for pros!).
A Get Going Fast Quick Installer can be found here : https://www.patreon.com/posts/fluxgym-web-ui-119476471
02:43 Finding repository
03:13 The Problem with Pinokio (Don't use it)
04:57 Manual Installation
24:10 Running FluxGym
24:44 Setting up Application
27:27 Loading & Captioning Images
30:31 Advanced Options
31:04 Auto Downloading Model
31:59 Training Process
34:12 Copying Lora to Image Generation Software
35:52 Loading Lora and Generating Image
37:29 Get Going Fast Installer
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------ Helpful Video Tutorials -----
VS Build Tools 2019 - Cleanest / Easiest Install Ever: https://youtu.be/TUS4A-XsAPo
Installing Cuda: https://youtu.be/_GpyoEbs3Hs
Installing CuDNN: https://youtu.be/RY2mEbi7PJc
Fresh AI Setup (Windows): https://youtu.be/4aCtOVcvcj4
Installing Miniconda: https://youtu.be/ULAVtKBOKXE
Installing Python: https://youtu.be/1CdeBbk9A2k
Installing Git: https://youtu.be/xxVOm3ndeSU
Installing WSL: https://youtu.be/3GNqg3GdEKA
Installing Llama.cpp: https://youtu.be/r-05yuXTEPE
