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---
# This configuration requires 48GB of VRAM or more to operate
job: extension
config:
# this name will be the folder and filename name
name: "my_first_flex_finetune_v1"
process:
- type: 'sd_trainer'
# root folder to save training sessions/samples/weights
training_folder: "output"
# uncomment to see performance stats in the terminal every N steps
# performance_log_every: 1000
device: cuda:0
# if a trigger word is specified, it will be added to captions of training data if it does not already exist
# alternatively, in your captions you can add [trigger] and it will be replaced with the trigger word
# trigger_word: "p3r5on"
save:
dtype: bf16 # precision to save
save_every: 250 # save every this many steps
max_step_saves_to_keep: 2 # how many intermittent saves to keep
save_format: 'diffusers' # 'diffusers'
datasets:
# datasets are a folder of images. captions need to be txt files with the same name as the image
# for instance image2.jpg and image2.txt. Only jpg, jpeg, and png are supported currently
# images will automatically be resized and bucketed into the resolution specified
# on windows, escape back slashes with another backslash so
# "C:\\path\\to\\images\\folder"
- folder_path: "/path/to/images/folder"
caption_ext: "txt"
caption_dropout_rate: 0.05 # will drop out the caption 5% of time
shuffle_tokens: false # shuffle caption order, split by commas
# cache_latents_to_disk: true # leave this true unless you know what you're doing
resolution: [ 512, 768, 1024 ] # flex enjoys multiple resolutions
train:
batch_size: 1
# IMPORTANT! For Flex, you must bypass the guidance embedder during training
bypass_guidance_embedding: true
# can be 'sigmoid', 'linear', or 'lognorm_blend'
timestep_type: 'sigmoid'
steps: 2000 # total number of steps to train 500 - 4000 is a good range
gradient_accumulation: 1
train_unet: true
train_text_encoder: false # probably won't work with flex
gradient_checkpointing: true # need the on unless you have a ton of vram
noise_scheduler: "flowmatch" # for training only
optimizer: "adafactor"
lr: 3e-5
# Paramiter swapping can reduce vram requirements. Set factor from 1.0 to 0.0.
# 0.1 is 10% of paramiters active at easc step. Only works with adafactor
# do_paramiter_swapping: true
# paramiter_swapping_factor: 0.9
# uncomment this to skip the pre training sample
# skip_first_sample: true
# uncomment to completely disable sampling
# disable_sampling: true
# ema will smooth out learning, but could slow it down. Recommended to leave on if you have the vram
ema_config:
use_ema: true
ema_decay: 0.99
# will probably need this if gpu supports it for flex, other dtypes may not work correctly
dtype: bf16
model:
# huggingface model name or path
name_or_path: "ostris/Flex.1-alpha"
is_flux: true # flex is flux architecture
# full finetuning quantized models is a crapshoot and results in subpar outputs
# quantize: true
# you can quantize just the T5 text encoder here to save vram
quantize_te: true
# only train the transformer blocks
only_if_contains:
- "transformer.transformer_blocks."
- "transformer.single_transformer_blocks."
sample:
sampler: "flowmatch" # must match train.noise_scheduler
sample_every: 250 # sample every this many steps
width: 1024
height: 1024
prompts:
# you can add [trigger] to the prompts here and it will be replaced with the trigger word
# - "[trigger] holding a sign that says 'I LOVE PROMPTS!'"\
- "woman with red hair, playing chess at the park, bomb going off in the background"
- "a woman holding a coffee cup, in a beanie, sitting at a cafe"
- "a horse is a DJ at a night club, fish eye lens, smoke machine, lazer lights, holding a martini"
- "a man showing off his cool new t shirt at the beach, a shark is jumping out of the water in the background"
- "a bear building a log cabin in the snow covered mountains"
- "woman playing the guitar, on stage, singing a song, laser lights, punk rocker"
- "hipster man with a beard, building a chair, in a wood shop"
- "photo of a man, white background, medium shot, modeling clothing, studio lighting, white backdrop"
- "a man holding a sign that says, 'this is a sign'"
- "a bulldog, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle"
neg: "" # not used on flex
seed: 42
walk_seed: true
guidance_scale: 4
sample_steps: 25
# you can add any additional meta info here. [name] is replaced with config name at top
meta:
name: "[name]"
version: '1.0'
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