Introduction
When it comes to training LoRA models on Flux (such as Flux Dev or Flux Schnell), one of the most challenging tasks can be generating high-quality, detailed captions for your image datasets. That’s where this easy-to-use Colab notebook comes in, offering a powerful yet simple solution for automatically captioning images using the Florence-2 model, perfect for Flux and SDXL models.
This Colab notebook is designed to run smoothly in a T4 environment with normal RAM, making it highly accessible for a wide range of users. Whether you’re new to AI art generation or a seasoned professional, this tool provides an efficient way to prepare your datasets without overloading resources.
Key Features:
Why This Matters for Flux and XL Models
Flux models, especially when used for style training or dataset preparation, thrive on detailed, contextual captions. Whether you are experimenting with hybrid appearances in SDXL models or training LoRAs with distinct style prompts, this Colab ensures consistent, high-quality captions with ease. It’s not just for LoRA training—SDXL models can also benefit from the seamless workflow, making it a great multi-purpose tool for captioning AI image datasets.
How to Use It
This notebook is truly a time-saving, efficient solution for anyone working with Flux models, SDXL, or LoRA training.