{
  "name": "Armless / double forequarter amputee",
  "slug": "armless-double-forequarter-amputee",
  "base_model": "Krea 2",
  "media_type": "image",
  "model_id": 1088883,
  "version_id": 3277710,
  "version_name": "krea2",
  "source": "civitai",
  "url": "https://civitai.com/models/1088883",
  "repo_id": null,
  "file_path": null,
  "author": "extrememittens",
  "category": {
    "key": "other",
    "label": "Uncategorised"
  },
  "modalities": [],
  "primary_modality": "unspecified",
  "checkpoint_family": "unknown",
  "trigger_words": [
    "doublefq",
    "armless"
  ],
  "recommended_settings": {},
  "chaining": {
    "author": {
      "stacks": "not stated",
      "notes": "",
      "avoid": [],
      "requires": [],
      "order": "",
      "strength": "",
      "stated": false
    },
    "general_rules": [
      "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": [
    "Well established — 1,887 downloads. [source: CivitAI stats]",
    "Positively received — 266 thumbs-up with no down-votes. [source: CivitAI stats]",
    "Explicit trigger word(s) — doublefq, armless — so the effect can be turned on and off from the prompt. [source: model metadata]",
    "Compact at 112 MB — cheap to stack with other LoRAs. [source: file size]"
  ],
  "cons": [
    "Author never states which generation mode it was trained for; test against your own workflow before relying on it. [source: description]",
    "Thin documentation — expect trial and error. [source: description length]"
  ],
  "file": {
    "name": "doublefq_krea2.safetensors",
    "size_bytes": 117454576,
    "size_mb": 112.01,
    "sha256": "1bc2b7c1b4842ba4427f6e42bb3ca00a9510f5e357d16fdf0d7db25eee820bd0"
  },
  "stats": {
    "downloads": 1887,
    "thumbs_up": 266,
    "thumbs_down": 0
  },
  "popularity": {
    "downloads": 1887,
    "thumbs_up": 266,
    "thumbs_down": 0,
    "comments": 0,
    "approval": "100% positive (266/266)",
    "age_days": 6.6,
    "downloads_per_day": 23.92,
    "rank_by_downloads": 118,
    "rank_by_momentum": 168,
    "of_total": 200,
    "adoption_tier": "Modest",
    "momentum": "Long tail · fresh release"
  },
  "selection_score": 86.0,
  "selection_reasons": [
    "1,887 downloads",
    "266 thumbs-up",
    "top-ranked for its category"
  ],
  "example_media": [],
  "tags": [
    "concept",
    "amputee",
    "body modification",
    "armless"
  ],
  "scraped_at": "2026-09-05T03:58:35+00:00",
  "path": "krea-2/armless-double-forequarter-amputee"
}