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XLabs-AI / x-flux

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FLUX Finetuning scripts

This repository provides training scripts for Flux model by Black Forest Labs.
XLabs AI team is happy to publish fune-tuning Flux scripts, including:

ComfyUI

See our github for comfy ui workflows. Example Picture 1

Requirements

  1. Python >= 3.10
  2. PyTorch >= 2.1
  3. HuggingFace CLI is required to download our models: huggingface-cli login

    Installation Guide

  4. Clone our repo: 
    git clone https://github.com/XLabs-AI/x-flux.git
  5. Create new virtual environment: 
    python3 -m venv xflux_env
source xflux_env/bin/activate
  6. Install our dependencies by running the following command: 
    pip install -r requirements.txt

Training

We trained LoRA and ControlNet models using DeepSpeed!
It's available for 1024x1024 resolution!

Models

We trained IP-Adapter, Canny ControlNet, Depth ControlNet, HED ControlNet and LoRA checkpoints for FLUX.1 [dev]
You can download them on HuggingFace:

Also, our models are avaiable at civit.ai

LoRA

accelerate launch train_flux_lora_deepspeed.py --config "train_configs/test_lora.yaml"

ControlNet

accelerate launch train_flux_deepspeed_controlnet.py --config "train_configs/test_canny_controlnet.yaml"

Training Dataset

Dataset has the following format for the training process:

├── images/
│    ├── 1.png
│    ├── 1.json
│    ├── 2.png
│    ├── 2.json
│    ├── ...

Example images/*.json file

A .json file contains "caption" field with a text prompt.

{
    "caption": "A figure stands in a misty landscape, wearing a mask with antlers and dark, embellished attire, exuding mystery and otherworldlines"
}

Inference

To test our checkpoints, you can use several options:

  1. Launch adapters in ComfyUI with our workflows, see our repo for more details
  2. Use main.py script with CLI commands
  3. Use Gradio demo with simple UI

Gradio

Launch gradio as follows:

python3 gradio_demo.py --ckpt_dir model_weights

Define --ckpt_dir as the folder location with the downloaded XLabs AI adapter weights (LoRAs, IP-adapter, ControlNets)

IP-Adapter

python3 main.py \
 --prompt "wearing glasses" \
 --ip_repo_id XLabs-AI/flux-ip-adapter --ip_name flux-ip-adapter.safetensors --device cuda --use_ip \
 --width 1024 --height 1024 \
 --timestep_to_start_cfg 1 --num_steps 25 \
 --true_gs 3.5 --guidance 4 \
 --img_prompt assets/example_images/statue.jpg

LoRA

Example Picture 1 prompt: "A girl in a suit covered with bold tattoos and holding a vest pistol, beautiful woman, 25 years old, cool, future fantasy, turquoise & light orange ping curl hair" Example Picture 2 prompt: "A handsome man in a suit, 25 years old, cool, futuristic"

python3 main.py \
 --prompt "A cute corgi lives in a house made out of sushi, anime" \
 --lora_repo_id XLabs-AI/flux-lora-collection \
 --lora_name anime_lora.safetensors \
 --use_lora --width 1024 --height 1024

Example Picture 3

python3 main.py \
 --use_lora --lora_weight 0.7 \
 --width 1024 --height 768 \
 --lora_repo_id XLabs-AI/flux-lora-collection \
 --lora_name realism_lora.safetensors \
 --guidance 4 \
 --prompt "contrast play photography of a black female wearing white suit and albino asian geisha female wearing black suit, solid background, avant garde, high fashion"

Example Picture 3

Canny ControlNet V3

python3 main.py \
 --prompt "cyberpank dining room, full hd, cinematic" \
 --image input_canny1.png --control_type canny \
 --repo_id XLabs-AI/flux-controlnet-canny-v3 \
 --name flux-canny-controlnet-v3.safetensors \
 --use_controlnet --model_type flux-dev \
 --width 1024 --height 1024  --timestep_to_start_cfg 1 \
 --num_steps 25 --true_gs 4 --guidance 4

Example Picture 1

python3 main.py \
 --prompt "handsome korean woman, full hd, cinematic" \
 --image input_canny2.png --control_type canny \
 --repo_id XLabs-AI/flux-controlnet-canny-v3 \
 --name flux-canny-controlnet-v3.safetensors \
 --use_controlnet --model_type flux-dev \
 --width 1024 --height 1024  --timestep_to_start_cfg 1 \
 --num_steps 25 --true_gs 4 --guidance 4

Example Picture 1

Depth ControlNet V3

python3 main.py \
 --prompt "handsome man in balenciaga style, fashion" \
 --image input_depth1.png --control_type depth \
 --repo_id XLabs-AI/flux-controlnet-depth-v3 \
 --name flux-depth-controlnet-v3.safetensors \
 --use_controlnet --model_type flux-dev \
 --width 1024 --height 1024 --timestep_to_start_cfg 1 \
 --num_steps 25 --true_gs 3.5 --guidance 3

Example Picture 2

python3 main.py \
 --prompt "a village in minecraft style, 3d, full hd" \
 --image input_depth2.png --control_type depth \
 --repo_id XLabs-AI/flux-controlnet-depth-v3 \
 --name flux-depth-controlnet-v3.safetensors \
 --use_controlnet --model_type flux-dev \
 --width 1024 --height 1024 --timestep_to_start_cfg 1 \
 --num_steps 25 --true_gs 3.5 --guidance 3

Example Picture 2

HED ControlNet V3

 python3 main.py \
 --prompt "A beautiful woman with white hair and light freckles, her neck area bare and visible" \
 --image input_hed1.png --control_type hed \
 --repo_id XLabs-AI/flux-controlnet-hed-v3 \
 --name flux-hed-controlnet-v3.safetensors \
 --use_controlnet --model_type flux-dev \
 --width 1024 --height 1024  --timestep_to_start_cfg 1 \
 --num_steps 25 --true_gs 3.5 --guidance 4

Example Picture 2

Low memory mode

Use quantized version Flux-dev-F8 to achieve lower VRAM usage (22 GB) with --offload and --model_type flux-dev-fp8 settings:

python3 main.py \
 --offload --model_type flux-dev-fp8 \
  --lora_repo_id XLabs-AI/flux-lora-collection --lora_name realism_lora.safetensors \
 --guidance 4 \
 --prompt "A handsome girl in a suit covered with bold tattoos and holding a pistol"

Example Picture 0

Accelerate Configuration Example

compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
  gradient_accumulation_steps: 2
  gradient_clipping: 1.0
  offload_optimizer_device: none
  offload_param_device: none
  zero3_init_flag: false
  zero_stage: 2
distributed_type: DEEPSPEED
downcast_bf16: 'no'
enable_cpu_affinity: false
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 8
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false

Models Licence

Our models fall under the FLUX.1 [dev] Non-Commercial License
Our training and infer scripts under the Apache 2 License

Near Updates

We are working on releasing new ControlNet weight models for Flux: OpenPose, Depth and more!
Stay tuned with XLabs AI to see IP-Adapters for Flux.

Follow Our Updates