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v1.2 (recommended):krea2_identity_edit_v1_2.safetensors— better face likeness on restaged subjects and higher fidelity across every skill, from a 1024 high-resolution pass (v1.1 had none). New capabilities: character reference-sheet use and creation, head / face / eye / person swap, outpainting, inpainting, and virtual try-on. With the v1.2 nodes it also gains the FIT reference geometry — mismatched source/output aspect ratios are handled automatically, so no more stretched or blurry results — and aref_boostfidelity dial (how hard the edit holds the reference; ~4 is a strong-likeness starting point). Requires the v1.2 nodes.Head / face / eye / person swap is trained on stablellama's MIT-licensedchange_eye_face_head_persondataset — thank you for making it available.Low-VRAM variants:..._v1_2_r128.safetensors(0.91GB) and..._v1_2_r64.safetensors(0.46GB) — SVD rank-reduced from v1.2 (>99% of the weight energy retained), near-identical quality.Prior versions remain available:..._v1_1.safetensors(+ its_r128/_r64variants) and the original..._v1.safetensors.
source_latent/image), the person is always
image 2 (source_latent_b/image_b). Swapping them sharply degrades
results (this matches the training layout).| Task type | Model | Steps | CFG |
|---|---|---|---|
| Most edits (add, recolor, restyle, re-stage) | Turbo | 8–12 | 1.0 |
| Removals / large deletions | Raw | 20 | 3.0 |
ref_boost (v1.2 nodes) is the fidelity dial — ~4 gives strong face/body
likeness (the example workflow ships at 4); >10 starts breaking removals; <1
loosens toward creative freedom.fit geometry (default) a mismatched
source/output aspect ratio is handled automatically. On v1/v1.1 weights or
crop (legacy), match the source AR — otherwise preservation degrades.grounding_px is a real dial. Lower values = stronger edit adherence
and more uniform scene changes; higher = stronger identity/likeness.
v1.1's trained range is 384–768 (768 default); 1024 often still works
nicely. If you get duplicated/split compositions ("double pictures"),
lower grounding_px — running far above the trained range is the most
common cause. (v1's trained range was 512–1536.)NOTICE).
Key points for users: commercial use is permitted under the license's revenue
threshold (§2.3, currently <$1M/yr — above that, contact Krea for an enterprise
license); deployments must implement reasonable content moderation (§4.2); AI
disclosure obligations apply where required (§4.3). This repository modifies
the Krea Model as permitted by §3; it is not endorsed by Krea.















