File size: 2,903 Bytes
1ba389d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
job: extension
config:
name: test_v1
process:
- type: 'textual_inversion_trainer'
training_folder: "out/TI"
device: cuda:0
# for tensorboard logging
log_dir: "out/.tensorboard"
embedding:
trigger: "your_trigger_here"
tokens: 12
init_words: "man with short brown hair"
save_format: "safetensors" # 'safetensors' or 'pt'
save:
dtype: float16 # precision to save
save_every: 100 # save every this many steps
max_step_saves_to_keep: 5 # only affects step counts
datasets:
- folder_path: "/path/to/dataset"
caption_ext: "txt"
default_caption: "[trigger]"
buckets: true
resolution: 512
train:
noise_scheduler: "ddpm" # or "ddpm", "lms", "euler_a"
steps: 3000
weight_jitter: 0.0
lr: 5e-5
train_unet: false
gradient_checkpointing: true
train_text_encoder: false
optimizer: "adamw"
# optimizer: "prodigy"
optimizer_params:
weight_decay: 1e-2
lr_scheduler: "constant"
max_denoising_steps: 1000
batch_size: 4
dtype: bf16
xformers: true
min_snr_gamma: 5.0
# skip_first_sample: true
noise_offset: 0.0 # not needed for this
model:
# objective reality v2
name_or_path: "https://civitai.com/models/128453?modelVersionId=142465"
is_v2: false # for v2 models
is_xl: false # for SDXL models
is_v_pred: false # for v-prediction models (most v2 models)
sample:
sampler: "ddpm" # must match train.noise_scheduler
sample_every: 100 # sample every this many steps
width: 512
height: 512
prompts:
- "photo of [trigger] laughing"
- "photo of [trigger] smiling"
- "[trigger] close up"
- "dark scene [trigger] frozen"
- "[trigger] nighttime"
- "a painting of [trigger]"
- "a drawing of [trigger]"
- "a cartoon of [trigger]"
- "[trigger] pixar style"
- "[trigger] costume"
neg: ""
seed: 42
walk_seed: false
guidance_scale: 7
sample_steps: 20
network_multiplier: 1.0
logging:
log_every: 10 # log every this many steps
use_wandb: false # not supported yet
verbose: false
# You can put any information you want here, and it will be saved in the model.
# The below is an example, but you can put your grocery list in it if you want.
# It is saved in the model so be aware of that. The software will include this
# plus some other information for you automatically
meta:
# [name] gets replaced with the name above
name: "[name]"
# version: '1.0'
# creator:
# name: Your Name
# email: [email protected]
# website: https://your.website
|