osbarcelos79/x-flux

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

• LoRA 🔥
• ControlNet 🔥

ComfyUI

See our github for comfy ui workflows.

Requirements

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

Installation Guide

1. Clone our repo:

git clone https://github.com/XLabs-AI/x-flux.git

2. Create new virtual environment:

python3 -m venv xflux_env
source xflux_env/bin/activate

3. 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:

• flux-ip-adapter
• flux-controlnet-collections
• flux-controlnet-canny
• flux-RealismLora
• flux-lora-collections
• flux-furry-lora

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, use commands presented below.

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

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" 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

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"

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

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

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

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

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

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"

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.