loras-krea-2 / uglifier /info.txt
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Add 12 LoRA(s): ogipote-pote-style, uglifier, rly-thot-shot-jada-krea-2-ideogram-4-zib-zit-k9b, puckered-lips-shs-sdxl-pony-flux-krea2…
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UGLIFIER
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IDENTITY
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Base model Krea 2
Generation mode not declared by the author
Checkpoint not determined β€” verify before use
Category Uncategorised
Author zwaetschge
Source https://civitai.com/models/483303
Provenance CivitAI Β· model 483303 Β· version 3255143
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WEIGHTS
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File uglifier_epoch_20.safetensors
Version v1.0 K2
Size 218.0 MB
Format SafeTensor / unknown precision
SHA256 bb61510bf97da2f3f20c033dc7eb4082d08bcf90e3c408f2bbf6c4b7eda73268
Published 2026-08-22
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TRIGGER WORDS
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β€Ί "ugly"
β€Ί "big nose"
β€Ί "bad teeth"
β€Ί "pimples"
β€Ί "bad skin"
β€Ί "bald"
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RECOMMENDED SETTINGS
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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..
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ADOPTION & POPULARITY
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Downloads 5,062
Rating 100% positive (407/407)
Comments 0
Published 14 days ago
Download rate 35.0/day since release
Adoption rank #114 of 150 in this collection (Niche)
Momentum rank #69 of 150 by download rate (Steady Β· 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.
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CHAINING / STACKING
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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):
β€’ 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.
β€’ 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.
β€’ 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."
β€’ 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."
β€’ 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.
β€’ 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.
β€’ 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.
β€’ 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.
β€’ 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.
β€’ 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
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PROS
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+ Widely adopted β€” 5,062 downloads. [source: CivitAI stats]
+ Positively received β€” 407 thumbs-up with no down-votes. [source:
CivitAI stats]
+ Explicit trigger word(s) β€” ugly, big nose, bad teeth, pimples, bad
skin, bald β€” so the effect can be turned on and off from the prompt.
[source: model metadata]
+ Compact at 218 MB β€” cheap to stack with other LoRAs. [source: file
size]
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CONS & CAVEATS
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- Author never states which generation mode it was trained for; test
against your own workflow before relying on it. [source: description]
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COMPATIBILITY WARNING
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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.
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AUTHOR'S DESCRIPTION
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Disclaimer: All persons in the dataset used to train these models were
completely synthetic and none of these models are based on real persons.
The purpose of this model is to generate really ugly people.
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VERSION NOTES
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New Dataset based on Midjourney V8.2
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EXAMPLE MEDIA
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6 preview(s) in ./example_images/ β€” 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, 768x1376)
02_image.jpeg (image, 768x1376)
03_image.jpeg (image, 1448x1086)
04_image.jpeg (image, 1088x1928)
05_image.jpeg (image, 1088x1928)
06_image.jpeg (image, 1088x1928)
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HOW TO USE (COMFYUI)
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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.
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Scraped by lorakit on 2026-09-05 00:17 UTC.
Stats and description are the author's; pros/cons are derived from the
evidence tagged beside each line.
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