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πŸš€ T2ITrainer

⚠️ Development Notice: Currently in active development - stability not guaranteed. Frequent updates - check changelogs regularly.

T2ITrainer is a diffusers based training script. It aims to provide simple yet implementation for lora training.

πŸ“… Recent Updates

  • 2025-06-27: Support kontext nf4 training
Rehosted an nf4 version flux kontext on https://huggingface.co/lrzjason/flux-kontext-nf4

Rehosted an nf4 version flux fill on https://huggingface.co/lrzjason/flux-fill-nf4

download nf4 version flux fill and use it for training could significantly decrease lora training VRAM requirement.

πŸ›‘οΈ Prerequisites

  • PyTorch: torch>=2.3.0+cu121 (CUDA 12.1 supported) PyPI

πŸ’» Supported Training Configurations

Model Type VRAM Requirements Status
Kolors 11GB GPU βœ… Supported
SD3.5 (FP16 BS1) 24GB GPU βœ… Supported
Flux Fill,Kontext 24GB GPU βœ… Supported

βš™οΈ Installation Guide

0. System Requirements

❗ Mandatory: Install Microsoft Visual C++ Redistributable if encountering DLL errors

1. Automated Setup

Recommended Method

  git clone https://github.com/lrzjason/T2ITrainer.git
  cd T2ITrainer
  setup.bat
  • Handles: Virtual Environment β€’ Dependency Installation β€’ Model Downloads

2. Manual Installation

Clone Repository 🌐

    git clone https://github.com/lrzjason/T2ITrainer.git
    cd T2ITrainer

Virtual Environment πŸ› οΈ

    python -m venv venv
    call venv\Scripts\activate
    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

Model Downloads πŸ“₯

    # Kolors
    huggingface-cli download Kwai-Kolors/Kolors --local-dir kolors_models/

    # NF4 Flux Fill for low gpu
    huggingface-cli download "lrzjason/flux-fill-nf4" --local-dir flux_models/fill/

    # skip if downloaded nf 4 Flux Fill
    huggingface-cli download "black-forest-labs/FLUX.1-fill-dev" --local-dir flux_models/fill/
    
    # SD3.5 Models
    huggingface-cli download "stabilityai/stable-diffusion-3.5-large" --local-dir "sd3.5L/"

    # NF4 Flux kontext
    huggingface-cli download "lrzjason/flux-kontext-nf4" --local-dir flux_models/kontext/

Folder Structure

flux_models:

flux_models

kontext:

kontext

πŸš€ Launch Options

Script Command Special Notes
Flux kontext python ui_flux_fill.py Requires diffusers>=0.32.0, 24GB VRAM Recommended
Flux Fill python ui_flux_fill.py Requires diffusers>=0.32.0, 24GB VRAM Recommended
Kolors python ui.py Needs Fixed VAE
SD3.5 Large python ui_sd35.py 24GB VRAM Recommended

πŸ”§ Parameter Configuration Guide

CivitAI Article


🌌 Flux Model Management

Kontext Model Installation

Inpainting Model Setup

  huggingface-cli download "lrzjason/flux-kontext-nf4" --local-dir flux_models/kontext/

For more details (example dataset):

Fill Model Installation (Skip if train kontext)

Inpainting Model Setup

  huggingface-cli download "lrzjason/flux-fill-nf4" --local-dir flux_models/fill/ 

For more details (example dataset):

Dev Model Download (Skip if train fill and kontext)

Dev Model Installation

  huggingface-cli download "black-forest-labs/FLUX.1-dev" --local-dir flux_models/dev/

βš™οΈ Flux Training Recommended Parameters

Category Settings
Base Configuration Rank 16, AdamW, Lr 1e-4
24GB GPU 512 resolution, Batch Size 1
VRAM Optimization Use nf4 based training
Precision bf16

πŸ’» VRAM Usage nf4

VRAM Peak

πŸ’» VRAM Usage (bf16, blocks_to_swap=10)

VRAM Peak
VRAM Low

πŸ”§ Kolors Testing & Integration

  • Kolors Workflow:

        # ComfyUI Plugins
        git clone https://github.com/kijai/ComfyUI-KwaiKolorsWrapper
        git clone https://github.com/MinusZoneAI/ComfyUI-Kolors-MZ
  • Configuration Guide: πŸ“– CivitAI Article

πŸ†˜ Troubleshooting

  • Kolors Black Image Issue: Ensure you're using FP16 Fixed VAE
  • VRAM Limitations: Adjust blocks_to_swap parameter (higher values reduce memory usage)
  • Windows DLL Errors: Verify VC++ Redistributable installation

Star History

Star History Chart

Old Change logs:

Recent Change Logs:

  • 2025-06-27: Support kontxt nf4 training

Sponsor:

  • Thanks to @sourceful support me making flux fill lora training script.

πŸ“¬ Contact

Sponsors me for more open source projects:

Buy me a coffee:

Buy Me a Coffee QR

WeChat:

WeChat QR

Acknowledgements:

  • Thanks for diffusers and Terminus Research Group
  • Thanks to minienglish1 and Freon in EveryDream Discord for the assistance.
  • Special thanks to kohya ss for references from the training codebase.
  • Thanks to Kblueleaf for coding reference on hunyuandit gradient checkpoint implementation.
  • Thanks to Kolors for the open-source checkpoint.
  • Thanks to comfyui for the wonderful codebase.
  • Thanks to emojiiii for the setup.bat script and other updates.
  • Thanks to Rohit Gandikota and related authors of Concept Sliders https://github.com/rohitgandikota/sliders

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