Train Flux Kontext LoRAs in Scenario

Welcome to this step-by-step tutorial on training Flux Kontext LoRAs in Scenario. Flux Kontext LoRAs introduce a completely new way to train custom editing models, not just to learn a style, but to understand how to *transform* one image into another, guided by text instructions. In this video, you’ll learn: * What makes Kontext LoRAs different from standard Flux LoRAs * How to prepare before/after image pairs and edit instructions * How to set up test prompts to evaluate your training * How to configure parameters and monitor progress * How to apply your trained model for consistent, precise transformations Try Scenario Today: https://app.scenario.com/ Our knowledge base: https://help.scenario.com/en/ 📚 Keep Learning with Our Other Tutorials: https://youtu.be/T8G73YoblQA?si=9JWheFhe1XwkFqr1 https://youtu.be/aQZpeeLUXWs https://youtu.be/v5mTB-Bggio --- Timestamps: 0:00 – Welcome to the tutorial 0:06 – What are Flux Kontext LoRAs? 0:15 – Understanding transformation-based training 0:22 – Turning input images into guided outputs 0:28 – Why Kontext LoRAs are more powerful than base models 0:45 – Teaching transformations like pose, angle, and style 0:55 – How training differs from standard Flux LoRAs 0:59 – Training setup explained 1:06 – The “before,” “after,” and “instruction” structure 1:17 – Real editing commands, not captions 1:25 – Example: Rendering sketches into full-color scenes 1:31 – Curating your dataset 1:37 – Choosing high-quality before/after pairs 1:44 – How many pairs you need for strong results 1:50 – Accessing Scenario’s training interface 1:54 – Navigating to Create → Train 1:58 – Selecting Flux Kontext as base model 2:03 – Uploading your images 2:07 – Pairing before and after images 2:11 – Writing your edit instructions 2:20 – Keeping instructions consistent 2:25 – Example of clear instructions 2:34 – Using trigger words correctly 2:39 – Setting up test prompts and pairs 2:46 – Why use all 4 test slots 2:54 – Uploading test inputs and instructions 3:03 – Comparing epochs and outputs 3:13 – Configuring training parameters 3:23 – When to use auto settings 3:31 – Starting the training 3:34 – How long the process takes 3:41 – Previewing progress with test images 3:53 – Comparing different epochs 4:00 – Accessing your trained LoRA 4:07 – Using the model in Edit with Prompts 4:16 – Uploading your test image 4:22 – Writing matching instructions 4:27 – Getting consistent transformations 4:35 – What Kontext LoRAs enable 4:47 – Use cases: style, pose, brand integration, refinements 4:59 – Creative control and precision 5:03 – Check the knowledge base for examples 5:08 – Outro / Thanks for watching #lora #kontext #nanobanana #gemini #ai #editing