add NOOB config

configs/NOOB.knf.yaml

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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.
+
+    # -- Generated artifact filenames written into TRAINING/<config-id>_<run>.
+    config_filename: simpletuner-config.json                  # Top-level SimpleTuner config.
+    data_backend_filename: simpletuner-multidatabackend.json  # Multi-databackend config.
+
+    # Generated cache/output directories. Relative paths resolve below TRAINING/<config-id>_<run>.
+    cache_root: .simpletuner-cache  # Shared model, text, and VAE cache root.
+    output_dir: _simpletuner-output # Normal full-run checkpoint output dir.
+
+    # Subset-specific SimpleTuner dataloader overrides. Any key here is merged
+    # into the subset backend entry after the dataset defaults below.
+    subsets:
+      felkin_anchor:
+        probability: 1          # 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: 8          # 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: 2          # Sample head/face details at extra exposure.
+        crop: false             # Preserve detail framing; many samples are close crops.
+      genitals:
+        probability: 4          # 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
+      filename: simpletuner-validation-prompts.json
+      positive_prefix: "masterpiece, best quality, newest, "
+      from_manifest:
+        profile: tag
+        seed: 42
+        activation_token: Rook_Kaefer
+        species_token: felkin
+        negative_control_species: wolf
+      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.
+
+      # Converted full SDXL Diffusers directory from the WSL ComfyUI model store.
+      pretrained_model_name_or_path: /mnt/wsl/comfyui-models/models/checkpoints/_base_finetunes/willysRealism_coreV1Diffusers
+      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.
+
+    # == Curricular warmup
+    subset_warmup:
+      enabled: true
+      subsets: [fullbody, head]
+      steps: 800 # !! First steps of the total run are ONLY listed subsets when enabled!
+
+    # 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: 0.0002              # 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: 100
+      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: 2500          # Current short SDXL run length.
+
+      caption_dropout_probability: 0.0 # 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: 5   # Keep latest 5 checkpoints.
+      checkpoint_step_interval: 200    # Save checkpoint every 200 steps.
+      validation_step_interval: 200    # Run validation every 200 steps.
+      # validation_on_startup: true  # 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: 30     # Full-run validation sampling steps.
+      validation_guidance_real: 7.5          # SDXL validation guidance.
+      # validation_guidance: 5.0             # Alternative CFG field for some SimpleTuner versions.
+      # 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:
+      output_dir: _simpletuner-output-testrun # Keep smoke checkpoints away from full run.
+      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.