herraw/info.txt

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  HERRAW
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───────────────────────────────────────────────────────────────────────────────
  IDENTITY
───────────────────────────────────────────────────────────────────────────────
  Base model        Krea 2
  Generation mode   not declared by the author
  Checkpoint        not determined — verify before use
  Category          Visual style
  Author            VividMuse
  Source            https://civitai.com/models/2863032
  Provenance        CivitAI · model 2863032 · version 3262152

───────────────────────────────────────────────────────────────────────────────
  WEIGHTS
───────────────────────────────────────────────────────────────────────────────
  File              HerRAW-v0.2.safetensors
  Version           v2.0
  Size              223.8 MB
  Format            SafeTensor / unknown precision
  SHA256            eb40e42e2ce78bcd751d35f67033392cfa9bcabdbc005dfb381f638243669ffc
  Published         2026-08-24

───────────────────────────────────────────────────────────────────────────────
  TRIGGER WORDS
───────────────────────────────────────────────────────────────────────────────
  No trigger word. The LoRA applies as soon as it is loaded —
  strength is the only way to dial the effect up or down.

───────────────────────────────────────────────────────────────────────────────
  RECOMMENDED SETTINGS
───────────────────────────────────────────────────────────────────────────────
  Taken verbatim from the author's description:

  Sampler steps       8–12

───────────────────────────────────────────────────────────────────────────────
  ADOPTION & POPULARITY
───────────────────────────────────────────────────────────────────────────────
  Downloads               825
  Rating                  100% positive (74/74)
  Comments                0
  Published               12 days ago
  Download rate           45.8/day since release

  Adoption rank           #168 of 200 in this collection  (Niche)
  Momentum rank           #84 of 200 by download rate  (Steady · fresh release)

  Adoption tier is the percentile of total downloads within this collection;
  momentum is the percentile of downloads-per-day since release. Momentum is
  ranked rather than measured against a fixed rate, because this base model
  is itself new and every LoRA looks fast on an absolute scale. Both numbers
  are CivitAI's, read on the scrape date at the foot of this file.

───────────────────────────────────────────────────────────────────────────────
  CHAINING / STACKING
───────────────────────────────────────────────────────────────────────────────
  Stacks with others      not stated

  The author gave no chaining guidance. The rules below are the
  general Krea 2 ones, not anything specific to this LoRA.

  General Krea 2 rules that apply here (see REFERENCE.txt):

  • The most important rule is not about chaining but about which
    checkpoint you chain onto: the official README says in bold "TRAIN on
    Raw and RUN on Turbo", and "We highly recommend using RAW for training
    LoRAs and applying them on Turbo for inference." LoRAs trained on Raw
    are stated to work well on Turbo.
  • Chain with LoraLoaderModelOnly nodes in series (model -> model). Krea 2
    LoRAs are DiT-only, so there is no CLIP side to chain and the text-
    encoder branch stays untouched however many LoRAs you add.
  • Krea 2 LoRAs stack in practice and the community treats multi-LoRA as
    routine - style + character, style + slider, realism + character.
    Several CivitAI Krea 2 authors state their LoRAs stack cleanly; one
    writes "I recently stacked over 20 of my own LoRAs on a single
    generation and the output still came out great."
  • Reduce per-LoRA strength when stacking. CivitAI Krea 2 authors converge
    on dropping from ~1.0 to roughly 0.6-0.9 once more than one adapter is
    loaded. The CivitAI 12GB training guide also notes rank affects
    composability: "rank 8 produced a lighter style influence that was
    easier to stack with other LoRAs, rank 16 provided a useful balance
    between concept strength and composability, and rank 32 was better
    suited to a precise object or concept intended to take priority over
    other stacked LoRAs."
  • Accelerator LoRAs are position-sensitive in intent, not in node order:
    a Raw-to-Turbo delta adapter belongs on the Raw checkpoint, a
    sub-8-step LoRA belongs on Turbo (or on Raw already carrying a Raw-to-
    Turbo adapter). Chaining Raw -> Raw-to-Turbo adapter -> 4-step LoRA is
    explicitly recommended by the 4-step LoRA's author.
  • Whatever you stack, the schedule must stay Turbo's: cfg 1.0 in ComfyUI
    (guidance 0.0 in diffusers) and mu/shift 1.15. The 4-step LoRA's card
    says "Keep mu = 1.15. The training targets are anchored to that grid; a
    different shift moves the [sampler off them]"; the same reasoning
    applies to any Turbo-trained adapter in the chain.
  • Reference/edit LoRAs are designed to be stacked under ordinary subject
    and style LoRAs - the Identity Edit card states "Composes with your
    LoRAs: character/body/style LoRAs stack on top and steer the prior" and
    recommends a stacked subject LoRA when unusual subjects drift toward
    the base prior.
  • Krea 2 LoRAs cannot be chained with LoRAs for any other base model.
    Many CivitAI pages carry multi-model titles like "(Krea-2 + ZIT)" or
    "[Flux | ZIB | Krea2]" - those are separate files for separate
    architectures shipped under one model page, not a combined adapter.
  • To combine two full Krea 2 checkpoints rather than adapters, ComfyUI
    ships a dedicated ModelMergeKrea2 node (added in v0.27.0) with per-
    section weights for first., tmlp., txtmlp., tproj.,
    txtfusion.projector, txtfusion.layerwise_blocks.0-1,
    txtfusion.refiner_blocks.0-1, blocks.0-27 and last.
  • The author never states which weight family this targets. Silent
    degradation, never a hard error, between Raw and Turbo. The two share
    one architecture - ai-toolkit's config is commented "The reference
    'single_mmdit_large_wide' architecture (oss_raw / oss_turbo share it)"
    - so every LoRA tensor shape matches on both and ComfyUI/diffuser

───────────────────────────────────────────────────────────────────────────────
  PROS
───────────────────────────────────────────────────────────────────────────────
  + Positively received — 74 thumbs-up with no down-votes. [source: CivitAI
    stats]
  + Compact at 224 MB — cheap to stack with other LoRAs. [source: file
    size]
  + Author published concrete recommended settings. [source: description]

───────────────────────────────────────────────────────────────────────────────
  CONS & CAVEATS
───────────────────────────────────────────────────────────────────────────────
  - Author labels this experimental — results vary shot to shot. [source:
    description]
  - No trigger word — the LoRA is always on once loaded, so strength is the
    only control. [source: model metadata]
  - Author never states which generation mode it was trained for; test
    against your own workflow before relying on it. [source: description]
  - Modest adoption (825 downloads) — less community feedback to rely on.
    [source: source stats]

───────────────────────────────────────────────────────────────────────────────
  COMPATIBILITY WARNING
───────────────────────────────────────────────────────────────────────────────
  Silent degradation, never a hard error, between Raw and Turbo. The two
  share one architecture - ai-toolkit's config is commented "The reference
  'single_mmdit_large_wide' architecture (oss_raw / oss_turbo share it)" - so
  every LoRA tensor shape matches on both and ComfyUI/diffusers will load an
  adapter against either without complaint. The lvladikov 4-step LoRA card
  states this for the reverse direction: "Every layer it targets also exists
  in Krea 2 Raw, so it will load there without complaint - but that is a side
  effect of the shared architecture, not a supported mode", and reports
  mixed, subject-dependent results with malformed subjects (duplicated heads,
  fused limbs) at low step counts, needing 14+ steps with Raw's CFG on before
  output is coherent. The intended direction (train on Raw, run on Turbo) is
  officially blessed. The more common practical failure is a settings
  mismatch rather than a weight mismatch: running a Turbo-targeted LoRA at
  Raw's 52 steps + CFG 3.5, or leaving CFG enabled on Turbo, degrades output
  with no warning. Loading a Krea 2 LoRA against a different model family
  entirely (Flux, Qwen-Image, Z-Image) is also not an error - ComfyUI logs
  "lora key not loaded: {key}" per key and generates as if no LoRA were
  applied.

───────────────────────────────────────────────────────────────────────────────
  AUTHOR'S DESCRIPTION
───────────────────────────────────────────────────────────────────────────────
  Recommend:
  Sampler: ddim Scheduler: beta/beta57(for more realistic) Steps: 8 - 12

  HerRAW 是一个面向 Krea 2 的通用女性真实摄影 LoRA，目标是在尽量保持原始
  Prompt、人物特征、构图和场景控制能力的前提下，提升女性人像的自然摄影质感。
  本模型 无需触发词 。加载 LoRA 后，可以直接使用正常的自然语言 Prompt 进行生成。
  v0.1 是 HerRAW 的第一版实验性基线模型，主要用于验证数据训练通用女性摄影 LoRA 的可行性。

  HerRAW is a general-purpose female photography LoRA for Krea 2, designed to
  improve natural photographic realism while preserving as much of the
  original prompt, subject characteristics, composition, and scene control as
  possible.
  The model requires no trigger word . Simply load the LoRA and use normal
  natural-language prompts.
  v0.1 is the first experimental baseline of HerRAW and is primarily intended
  to evaluate the feasibility of building a general female photography LoRA
  from training data.

───────────────────────────────────────────────────────────────────────────────
  VERSION NOTES
───────────────────────────────────────────────────────────────────────────────
  What’s improved
  - Better face diversity — less tendency for different characters to
  converge toward the same face.

  - More natural skin — reduced overly smooth / plastic-looking skin, with
  more believable texture, tonal variation, and highlights.

  - Improved East Asian facial aesthetics — more balanced and natural-looking
  features without forcing a fixed AI beauty template.

  - Stronger photographic realism — improved hair, clothing materials,
  lighting, and overall realism in close-ups, half-body, full-body, and
  environmental portraits.

  相比 0.1：
  - 人脸多样性更好 ：减少不同人物逐渐长得相似的问题，更好地保留原本的脸型和气质。

  - 肤质更加自然 ：降低磨皮感和塑料感，增加更真实的肤色变化、皮肤纹理和高光表现。

  - 东亚女性面部更协调 ：提升整体审美，同时尽量避免固定的“AI 美女脸”。

  - 整体摄影感更完整 ：发丝、衣料、光线以及半身、全身、环境人像都有进一步改善。

───────────────────────────────────────────────────────────────────────────────
  EXAMPLE MEDIA
───────────────────────────────────────────────────────────────────────────────
  6 preview(s) in ./example_images/ — community results for
  this LoRA. Videos keep a matching _poster.jpg still frame.

  No prompts are recorded below: CivitAI's public API flags these posts as
  having generation metadata but does not return it, so the prompts cannot be
  scraped. Open the model page to read them.

  01_image.jpeg  (image, 1536x2048)
  02_image.jpeg  (image, 1536x2048)
  03_image.jpeg  (image, 1448x2176)
  04_image.jpeg  (image, 1448x2176)
  05_image.jpeg  (image, 1536x2048)
  06_image.jpeg  (image, 3552x5280)

───────────────────────────────────────────────────────────────────────────────
  HOW TO USE (COMFYUI)
───────────────────────────────────────────────────────────────────────────────
  1. Update ComfyUI to at least v0.26.0 (released 2026-06-23), which added
  local Krea2 support. For reference-image / style-reference / edit LoRAs you
  need at least v0.29.0 (2026-07-29), which added regular and timestep-zero
  reference images for Krea 2. ModelMergeKrea2 arrived in v0.27.0
  (2026-06-30).

  2. Put the base stack in place (files from huggingface.co/Comfy-Org/Krea-2,
  which is not gated):
     - ComfyUI/models/diffusion_models/krea2_turbo_fp8_scaled.safetensors
  (documented recommended default; the repo also holds krea2_turbo_bf16,
  _int8_convrot, _mxfp8, _nvfp4 and krea2_raw_bf16 / _fp8_scaled /
  _int8_convrot)
     - ComfyUI/models/text_encoders/qwen3vl_4b_fp8_scaled.safetensors (bf16
  also available)
     - ComfyUI/models/vae/qwen_image_vae.safetensors

  3. Put the LoRA .safetensors in ComfyUI/models/loras/ - flat, no per-model
  subfolder required.

  4. Build or load the graph. The official image_krea2_turbo_t2i.json
  template is: UNETLoader (krea2_turbo_fp8_scaled.safetensors) ->
  LoraLoaderModelOnly -> KSampler; CLIPLoader
  (qwen3vl_4b_fp8_scaled.safetensors, type "krea2") -> text encode ->
  KSampler positive, with ConditioningZeroOut into negative; VAELoader
  (qwen_image_vae.safetensors) -> VAEDecode -> SaveImage; EmptyLatentImage
  1024x1024 driven by ResolutionSelector. An int8 sibling template
  (image_krea2_turbo_t2i_int8.json) also ships.

  5. Load the LoRA with LoraLoaderModelOnly, not LoraLoader - both official
  templates do. Krea 2 LoRAs patch the DiT only; note that the DiT's own
  text_fusion / txtfusion blocks are a normal LoRA target (the official style
  LoRAs patch them), but the Qwen3-VL text encoder itself is not. Set
  strength 1.0 for Krea's official style LoRAs (the shipped template uses
  0.8) and add the LoRA's trigger word to the prompt.

  6. Sampler settings: steps 8, cfg 1, sampler euler, scheduler simple,
  denoise 1.0. Do not add a ModelSampling node for plain t2i - ComfyUI
  already applies shift 1.15 from Krea2.sampling_settings.

  7. For style reference, use the dedicated template: UNETLoader
  krea2_turbo_int8_convrot.safetensors, LoraLoaderModelOnly
  krea2_style_reference.safetensors at 1.0, ModelSamplingFlux (1.15, 0.5),
  TextEncodeQwenImageEditPlus fed by LoadImage,
  FluxKontextMultiReferenceLatentMethod set to index_timestep_zero, and
  SamplerCustomAdvanced with KSamplerSelect euler + BasicScheduler simple/8 +
  CFGGuider cfg 1.

  8. For instruction editing (Krea 2 Identity Edit), stock nodes are not
  enough: install the ComfyUI-Krea2Edit node pack, which ships its own
  workflows, and run Turbo at 8-12 steps / cfg 1 (or Raw at 20 steps / cfg 3
  for removals) with LoRA strength 1.0.

  9. Low-VRAM alternative: install city96's ComfyUI-GGUF and use a community
  GGUF build (realrebelai/KREA-2_GGUFs, quantized from Turbo;
  molbal/krea2-gguf, quantized from Raw) with the Unet Loader (GGUF) node in
  place of UNETLoader. There is no official GGUF release. LoRA loading is
  unchanged.

───────────────────────────────────────────────────────────────────────────────
  Scraped by lorakit on 2026-09-05 03:59 UTC.
  Stats and description are the author's; pros/cons are derived from the
  evidence tagged beside each line.
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