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# == Directories
# ==============================================================
# > Dataset sync derives SOURCE/, MANIFEST.knf.xlsx, and HF/<config-id>/ from this filename.
# -- Map exported subset names to source subfolders in MANIFEST.knf.xlsx.
mappings:
# > Anchor identity examples get sampled at a lower probability below.
felkin_anchor:
- "0-ANCHOR" # Source folder for anchor identity images.
# > Explicit anatomy close-up subsets are kept separate for sampling control.
genitals:
- "6-DICK" # Source folder for exposed anatomy close-ups.
- "6-SHEATH" # Source folder for sheathed anatomy close-ups.
# > Complete body.
fullbody:
- "0-FULLBODY" # Full-body identity examples; also included in rest subset.
- "99-VERSION-LEANER" # Alternate leaner full-body examples.
# > General body, hand, leg, tail, and leaner variant images.
body_details:
- "1-TORSO" # Torso detail examples.
- "3-HANDS" # Hand detail examples.
- "4-LEGS" # Leg/foot detail examples.
- "5-TAIL" # Tail detail examples.
# > Focused fur-texture crops derived from high-resolution Rook sources.
fur:
- "7-FUR" # Fur crops for coat, mane, spots, paws, tail, and anatomy-adjacent texture.
head:
- "2-HEAD" # Face/head detail examples.
# > Also export manifest rows marked sfw into an additional generated sfw subset.
export_sfw_subset: false # < Keep NOOB focused on the explicit mapped subsets.
# ==============================================================
# == Images
# ==============================================================
# Export-time mirroring writes fixed extra image/caption pairs before
# SimpleTuner sees the dataset. flip_only keeps kneifftools from applying its
# own random crop, rotation, or color jitter.
augmentations:
mirrored_extra: true # Add one mirrored copy per selected source image.
mirrored_transform: flip_only # Exact horizontal mirror, no kneifftools crop/jitter.
seed: 12345 # Makes mirrored export naming deterministic.
# Export image area bounds before SimpleTuner sees the dataset.
image_resize:
min_pixel_area: 512 # Upscale tiny images below roughly 512x512 area.
max_pixel_area: 1024 # Downscale large images above roughly 1024x1024 area.
# ==============================================================
# == Captions
# ==============================================================
# Controlled caption rendering context used by all generated sidecars.
caption:
subject_sex: male # Adds male subject wording to prose renderers.
add_domains_to_tags: false # SDXL tag captions should stay plain, not domain-prefixed.
# NOOB uses SDXL-style tag captions. Use one .txt sidecar per image so
# SimpleTuner's textfile strategy reads the intended caption directly.
caption_outputs:
mode: hybrid_txt # One .txt sidecar per image containing selected formats.
formats: [tag] # Tag-only captions for NOOB/SDXL training.
tag_scope: all # Keep the full tag tail, including identity and anatomy tags.
# Optional per-subset caption output overrides. Keep commented unless a subset
# needs different caption files or formats.
# caption_outputs_overrides:
# felkin_anchor:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# genitals:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# fullbody:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# body_details:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# fur:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# head:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# sfw:
# mode: hybrid_txt
# formats: [tag]
# tag_scope: all
# ==============================================================
# == Publishing
# ==============================================================
publishing:
huggingface:
enabled: true # Generate dataset-card metadata during dataset sync.
repo_id: null # Optional Hugging Face dataset repo id.
pretty_name: Rook NOOB SDXL LoRA # Human-readable dataset-card base title.
version: null # Public dataset version label.
optimized_for_model: Willys Noob Realism Core V1 # Rendered as [For Willys Noob Realism Core V1].
license: null # Optional dataset license.
tags: [sdxl, noob, lora] # Dataset-card tags.
provenance: null # Optional dataset provenance note.
adult_content: false # Render the adult-content notice in README.md.
notes: null # Optional free-form dataset-card notes.
# ==============================================================
# == LoRA Training
# ==============================================================
training:
enabled: true # Enables kneifftools training artifact generation.
backend: simpletuner # Selects the SimpleTuner LoRA backend.
simpletuner:
enabled: true # Optional backend-specific switch; defaults to enabled.
# Subset-specific SimpleTuner dataloader overrides. Any key here is merged
# into the subset backend entry after the dataset defaults below.
subsets:
felkin_anchor:
probability: 0.01 # Sample anchor identity images at steady exposure.
crop: false # Preserve full source composition.
# repeats: 0 # Optional per-subset repeat count.
# disabled: false # Optional per-subset on/off switch.
fullbody:
probability: 10 # Sample full-body subset at high probability.
crop: false # Preserve full-body composition.
# repeats: 0
# disabled: false
body_details:
probability: 4 # Sample body detail subset at normal probability.
crop: false # Preserve detail framing; many samples are already close crops.
# repeats: 0
# disabled: false
fur:
probability: 1 # Give focused fur crops extra exposure.
crop: false # Preserve texture crop intent; do not random-crop fur samples.
# repeats: 0
# disabled: false
head:
probability: 3 # Sample head/face details at extra exposure.
crop: false # Preserve detail framing; many samples are close crops.
genitals:
probability: 3 # Sample anatomy subset at normal probability.
crop: false # Preserve anatomy crop framing.
# repeats: 0
# disabled: false
# Dataset backend defaults copied into every image subset entry.
dataset:
type: local # SimpleTuner local filesystem backend.
dataset_type: image # Image dataset backend, not text embeds.
resolution: 1024 # Target area edge; pixel_area means 1024^2 area.
minimum_image_size: 512 # SimpleTuner lower bound for SDXL image handling.
maximum_image_size: 1024 # Upper bound for input image sizing.
target_downsample_size: 1024 # Downsample target for cache generation.
resolution_type: pixel_area # Area-based buckets, not smaller-edge resize.
caption_strategy: textfile # Read captions from exported .txt sidecars.
metadata_backend: discovery # Discover images/captions from directories.
crop: false # Default only; every configured subset disables crop above.
crop_style: random # Inert for crop:false subsets.
crop_aspect: preserve # Preserve original aspect instead of square crop.
repeats: 0 # Dataset-level repeat count; subset can override.
disabled: false # Dataset-level backend switch.
# Optional shared text-embedding backend overrides. Commented keys show the
# kneifftools-owned defaults for the generated text_embeds backend.
text_embeds:
id: text-embeds # Backend id used by SimpleTuner.
type: local # Store embeddings on local filesystem.
dataset_type: text_embeds
default: true # Marks this as the shared embedding backend.
# cache_dir: .simpletuner-cache/text # Override generated text cache dir.
disabled: false
# Generate a SimpleTuner user_prompt_library JSON from manifest-sampled tag
# prompts plus a few stable NOOB probes.
validation_prompts:
enabled: true
positive_prefix: "masterpiece, best quality, newest, "
from_manifest:
profile: tag
seed: 42
custom:
noob_safe_portrait: "Rook_Kaefer, felkin, fur, red fur, black spots, spotted fur, fur markings, close-up portrait, detailed lighting"
noob_safe_fullbody_reference: "Rook_Kaefer, felkin, fur, red fur, black spots, spotted fur, fur markings, musclegut, full-body character reference, standing, solo"
noob_safe_fur_detail: "Rook_Kaefer, felkin, fur, red fur, black spots, spotted fur, fur markings, musclegut, fur texture reference, mane, tail, paws"
noob_explicit_anatomy_reference: "Rook_Kaefer, felkin, fur, red fur, black spots, spotted fur, fur markings, musclegut, nude anatomy reference, sheath detail, clean lighting"
# Model and LoRA settings merged into the top-level SimpleTuner config.
model:
model_type: lora # Train a LoRA adapter.
model_family: sdxl # Use SimpleTuner's SDXL model family.
model_flavour: null # Loaded from a local SDXL checkpoint.
lora_rank: 64 # LoRA rank/capacity.
lora_alpha: 64 # LoRA alpha scaling.
lora_type: standard # Standard LoRA, not an alternate adapter type.
lora_format: diffusers # SDXL LoRA format expected by SimpleTuner for this run.
flux_lora_target: null # Remove the Flux/Chroma default from generated config.
# Train against the clean NOOB SDXL Diffusers base for adapter compatibility.
# Willy stays the intended downstream inference/showcase base after export.
pretrained_model_name_or_path: /mnt/wsl/comfyui-models/models/checkpoints/_base_finetunes/noobaiXLNAIXL_epsilonPred11Version
pretrained_unet_model_name_or_path: null
pretrained_vae_model_name_or_path: madebyollin/sdxl-vae-fp16-fix
pretrained_transformer_model_name_or_path: null
pretrained_t5_model_name_or_path: null
pretrained_text_encoder_model_name_or_path: null
# Precision defaults for SDXL LoRA training.
base_model_precision: no_change
base_model_default_dtype: bf16
mixed_precision: bf16
# init_lora: /path/to/existing.safetensors # Optional LoRA resume/init weights.
# lycoris_config: /path/to/lycoris.json # Optional LyCORIS config path.
# == Curriculum
curriculum:
enabled: true
phases:
- name: focused_start
start_step: 0
subsets: [fullbody, head]
- name: full_mix
start_step: 1000 # !! From this step onward, all subsets are active.
subsets: all
# Full-run trainer config. trainer_testrun below overrides selected keys
# only when knf train prepare/start is called with --testrun.
trainer:
# tracker_project_name: kneifftools-lora-training # Experiment tracker project.
# tracker_run_name: ladybird-noob # Full-run tracker name.
# hub_model_id: ladybird-noob-lora # Optional Hub model id if push_to_hub is enabled.
optimizer: adamw_bf16 # BF16 AdamW optimizer.
learning_rate: 0.00015 # SDXL LoRA learning rates fall between 1e-4 and 5e-4
lr_scheduler: constant_with_warmup # Ramp up LR to avoid weird color biases.
lr_warmup_steps: 200
seed: 42 # Training seed.
gradient_checkpointing: true # Reduce VRAM by recomputing activations.
# max_grad_norm: 1.0 # Optional gradient clipping.
# grad_clip_method: norm # Optional gradient clipping method.
train_batch_size: 4 # Per-device batch size.
gradient_accumulation_steps: 1 # Effective batch multiplier.
num_train_epochs: 0 # Step-based training; max_train_steps controls run length.
max_train_steps: 3200 # Current short SDXL run length.
caption_dropout_probability: 0.05 # Caption dropout for regularization.
data_backend_sampling: uniform # Uniform dataloader sampling.
allow_dataset_oversubscription: true
push_to_hub: false # Upload final artifacts to Hugging Face Hub.
push_checkpoints_to_hub: false # Upload intermediate checkpoints.
checkpoints_total_limit: 3 # Keep latest 5 checkpoints.
checkpoint_step_interval: 400 # Save checkpoint every 200 steps.
validation_step_interval: 400 # Run validation every 200 steps.
# disable_benchmark: false # Render baseline validation before training.
validation_prompt_library: false # Disable SimpleTuner built-in prompt library.
validation_disable_unconditional: true # Skip unconditional validation branch.
validation_resolution: 1024x1024 # Validation image size.
validation_num_inference_steps: 50 # Full-run validation sampling steps.
validation_guidance: 5.0 # SDXL CFG guidance used by validation.
validation_guidance_real: null # Remove flow-model real CFG from generated config.
validation_guidance_rescale: 0.0 # Guidance rescale; 0 disables rescale.
validation_seed: 42 # Deterministic validation seed.
num_eval_images: 1 # Images per validation prompt.
# validation_negative_prompt: "signature, ugly, cropped, blurry, low-quality"
report_to: none # Set to tensorboard to write TensorBoard logs.
# logging_dir: logs # TensorBoard log dir relative to TRAINING/<config-id>_<run>.
# Additional kneifftools-owned SimpleTuner defaults. Leave commented to
# use defaults from src/kneiff/training/lora/simpletuner.py.
use_ema: false
vae_batch_size: 1
aspect_bucket_alignment: 64
tokenizer_max_length: 77
t5_padding: null
fully_unload_text_encoder: true
offload_during_startup: true
keep_vae_loaded: false
resume_from_checkpoint: null
# Short smoke-run overrides. These merge last only with --testrun.
trainer_testrun:
max_train_steps: 4 # Tiny run to verify plumbing.
checkpoint_step_interval: 100 # Avoid extra smoke checkpoints.
validation_step_interval: 4 # Validate at the end of the smoke run.
ignore_final_epochs: true # Fix early stop due to SimpleTuner epoch calculation.
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