krea2-textfusion-refusal-reduction-lora/info.txt

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  KREA2 TEXTFUSION REFUSAL-REDUCTION LORA
═══════════════════════════════════════════════════════════════════════════════

───────────────────────────────────────────────────────────────────────────────
  IDENTITY
───────────────────────────────────────────────────────────────────────────────
  Base model        Krea 2
  Generation mode   not declared by the author
  Checkpoint        not determined — verify before use
  Category          Detail / anatomy fixer
  Author            Capitan01R
  Source            https://civitai.com/models/2775340
  Provenance        CivitAI · model 2775340 · version 3125118

───────────────────────────────────────────────────────────────────────────────
  WEIGHTS
───────────────────────────────────────────────────────────────────────────────
  File              Krea2_TextFusion_Refusal_Reduction.safetensors
  Version           v1.0
  Size              26.4 MB
  Format            SafeTensor / unknown precision
  SHA256            84ec722ddab93f6489c5315bca25de5dd1a7b7ec5045a3c4ce2f97f62e54e8e6
  Published         2026-07-13

───────────────────────────────────────────────────────────────────────────────
  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
───────────────────────────────────────────────────────────────────────────────
  The author did not publish specific settings.
  No author settings were published. Community baseline: steps Turbo: 8
  (official README and HF card CLI example; the ComfyUI template ships 8).
  Raw: 52 (official README). The krea-2 CLI's generic default is 28.
  Community Turbo LoRAs commonly suggest 8-12 (e.g. the Identity Edit card
  recommends Turbo at 8-12, or Raw at 20 for removals). A community 4-step
  LoRA on Turbo makes 4 valid; its author calls 2 steps an out-of-spec
  preview mode., cfg Turbo: CFG disabled - guidance_scale 0.0 in diffusers
  and --cfg 0.0 in the krea-2 CLI, which is cfg 1.0 in ComfyUI's KSampler
  (the official template ships cfg 1). These are the same thing; do not set
  ComfyUI cfg to 0. Raw: CFG 3.5 (official README; CLI generic default 4.5).
  Negative prompting on Turbo is effectively unused - the official templates
  route ConditioningZeroOut into the negative slot., sampler ComfyUI:
  KSampler with sampler euler, scheduler simple, denoise 1.0 (verified in
  image_krea2_turbo_t2i.json: [seed, 'randomize', 8, 1, 'euler', 'simple',
  1]). Timestep shift mu = 1.15 for Turbo; ComfyUI bakes this in via
  Krea2.sampling_settings = {"multiplier": 1.0, "shift": 1.15}, so the plain
  t2i template needs no ModelSampling node, while the style-reference
  template adds ModelSamplingFlux at max_shift 1.15 / base_shift 0.5. The CLI
  exposes --mu 1.15 for Turbo; Raw uses a resolution-derived mu interpolated
  between --y1 0.5 and --y2 1.15 (ai-toolkit mirrors this as base_shift 0.5 /
  max_shift 1.15 over image_seq_len 256-6400, exponential time shift).,
  resolution 1024x1024 default. Turbo: 1K-2K (the official CLI example
  generates 2048x2048; ComfyUI's ResolutionSelector defaults to 1 megapixel,
  set 2.0 for 2K). Raw: "trained to generate upto 1k resolution".
  Width/height are padded up to a multiple of 16., lora_strength 1.0 for
  Krea's nine official style LoRAs (docs.comfy.org lists Recommended Strength
  1.0 for every one), though the shipped t2i template's LoraLoaderModelOnly
  is set to 0.8. The style-reference LoRA is used at 1.0 in its template. The
  4-step distill LoRA documents 1.0 as its trained point, 1.0-1.5 as coherent
  extrapolation and above ~1.5 as speckle artefacting. Community subject
  LoRAs are typically recommended around 0.8-1.2 and dropped toward 0.6-0.9
  when several are stacked..

───────────────────────────────────────────────────────────────────────────────
  ADOPTION & POPULARITY
───────────────────────────────────────────────────────────────────────────────
  Downloads               29,758
  Rating                  100% positive (1702/1702)
  Comments                0
  Published               54 days ago
  Download rate           553.8/day since release

  Adoption rank           #19 of 150 in this collection  (High)
  Momentum rank           #1 of 150 by download rate  (Hot)

  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
───────────────────────────────────────────────────────────────────────────────
  + Widely adopted — 29,758 downloads. [source: CivitAI stats]
  + Positively received — 1,702 thumbs-up with no down-votes. [source:
    CivitAI stats]
  + Compact at 26 MB — cheap to stack with other LoRAs. [source: file size]

───────────────────────────────────────────────────────────────────────────────
  CONS & CAVEATS
───────────────────────────────────────────────────────────────────────────────
  - 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]

───────────────────────────────────────────────────────────────────────────────
  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
───────────────────────────────────────────────────────────────────────────────
  Progress update,
  the model refusal behaviour is deeper than the textfusion path, Dit blocks
  are included in this behaviour; therefore a LoRA alone CANNOT fix this
  issue, I am going to be working on a custom node that targets the DiT
  blocks without wrecking the model.

  V1.0 I recommend loading this LoRA with this LoRA Loader I just created :
  https://civitai.com/models/2844700/comfyui-sigmasync-lora
  Buy me a coffee :)

  # Krea2 TextFusion Refusal-Reduction LoRA
  This is a dedicated rank-64 LoRA trained with one narrow objective: reduce
  Krea2’s learned refusal and restriction behavior while preserving as much
  of the base model’s existing visual knowledge and prompt behavior as
  possible.
  This is not a concept, character, style, anatomy, or aesthetic LoRA. It was
  not trained to add new visual concepts, reproduce a training-image set, or
  impose a preferred look. Its training objective was exclusively to push the
  model away from refusal behavior so that concepts already represented
  within the base model are less likely to be suppressed during text
  conditioning.
  ## What It Changes
  Krea2 receives multiple hidden-state taps from its Qwen-VL text encoder and
  processes them through TextFusion before sending the resulting conditioning
  into the image transformer. This LoRA applies learned low-rank residuals
  only to the attention and internal MLP projections within:
  - txtfusion.layerwise_blocks.0
  - txtfusion.layerwise_blocks.1
  - txtfusion.refiner_blocks.0
  - txtfusion.refiner_blocks.1
  The release version deliberately contains no adapter for:
  - The TextFusion 1 × 12 tap projector
  - The external/general txtmlp
  - The image-transformer blocks or any other image-generation layers
  ## How It Works
  The base checkpoint is never overwritten. For every targeted linear layer,
  LoRA adds a learned rank-64 residual to the original weight during
  inference:
  W_effective = W_base + strength × ΔW
  This changes how existing Qwen-VL text features are routed, gated,
  transported, and refined through TextFusion before they reach Krea2’s
  untouched image transformer. In other words, the LoRA is intended to
  improve access to visual knowledge already present in the base model, not
  inject a new concept or replace the model’s learned visual representations.
  This release targets the specific TextFusion route isolated through layer-
  by-layer ablation instead of broadly amplifying activations or directly
  altering the projector.
  ## Usage
  Use strength of "1.00"

  Responsibility and Output Disclaimer
  This LoRA modifies the model’s text-conditioning behavior but does not
  determine, authorize, endorse, supervise, or control the images produced by
  individual users, prompts, workflows, checkpoints, samplers, or third-party
  software.
  Generated outputs remain dependent on the base model, user-provided
  conditioning, inference configuration, and the surrounding generation
  pipeline. The author assumes no responsibility or liability for what users
  choose to generate, how generated material is used, or whether any output
  complies with applicable laws, platform rules, licensing terms, or third-
  party rights.
  Users are solely responsible for their prompts, generated outputs,
  distribution decisions, and use of this LoRA.

───────────────────────────────────────────────────────────────────────────────
  VERSION NOTES
───────────────────────────────────────────────────────────────────────────────
  v.1.0.0 Krea 2 Turbo

───────────────────────────────────────────────────────────────────────────────
  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, 1024x1024)
  02_image.jpeg  (image, 832x1248)
  03_image.jpeg  (image, 1664x2432)
  04_image.jpeg  (image, 1664x2432)
  05_image.jpeg  (image, 832x1248)
  06_image.jpeg  (image, 1664x2432)

───────────────────────────────────────────────────────────────────────────────
  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 00:12 UTC.
  Stats and description are the author's; pros/cons are derived from the
  evidence tagged beside each line.
───────────────────────────────────────────────────────────────────────────────