Card: v2 trained on Turbo, the original on RAW

README.md

@@ -10,9 +10,18 @@ tags:
 
 # Unified Face Models
 
-One character file that works on more than one image model. `emmy-s5.char` carries FLUX.2
-reference images and a trained Krea 2 adapter in the same 107 MB container, so the same face
-renders on either model without keeping two sets of files in sync.
+Character files that work on more than one image model. Each one carries FLUX.2 reference images
+and a trained Krea 2 adapter in the same 107 MB container, so the same face renders on either
+model without keeping two sets of files in sync.
+
+| File | Krea 2 adapter trained on | Train resolution | Apply strength |
+| --- | --- | --- | --- |
+| `emmy-s500-v2.char` | Krea 2 **Turbo** (`krea2_turbo_bf16`) | 1024 | 0.5 |
+| `emmy-s5.char` | Krea 2 **RAW** (`krea2_raw_bf16`) | 512 | 1.0 |
+
+Same five references and same description in both, so their FLUX.2 side is identical. They differ
+only in how the Krea 2 adapter was trained, and both are published so the two can be compared on
+the same face.
 
 Built and trained on the canvas in [Inline Studio](https://github.com/inlineresearch/Inline-Studio).
 
@@ -32,7 +41,7 @@ to. The only way to give Krea 2 a persistent identity is a trained LoRA.
 A `.char` stores identity once and compiles a payload per model family:
 
 ```
-emmy-s5.char
+emmy-s500-v2.char
   manifest.json                        payload index, fingerprints, training record
   refs/000..004.png                    the 5 reference images, immutable
   derived/face_000..004.png            YuNet face crops at 512px
@@ -48,17 +57,31 @@ The references and the description are the truth. Everything under `payloads/` a
 cache and can be rebuilt from `refs/`. Adding a third model means adding a payload, not rebuilding
 the character.
 
-## What is in this one
+## What is in them
+
+Shared by both files:
 
 | | |
 | --- | --- |
 | References | 5 images, three at 2048px and two at 640px |
 | Trigger | `emmy4k woman with, natural unretouched skin, black hairs, fair skin` |
 | FLUX.2 payload | `flux2-klein`, 5 compiled references, max 1 MP, dimensions rounded to a multiple of 16 |
-| Krea 2 payload | `krea2-lora`, adapter fused at strength 1.0 |
+| Krea 2 payload | `krea2-lora`, one 183 MB adapter |
 
 ### Krea 2 training
 
+`emmy-s500-v2.char`, trained on Turbo:
+
+| | |
+| --- | --- |
+| Base | `krea2_turbo_bf16.safetensors` (Krea 2 Turbo) |
+| Steps | 500 |
+| Rank | 16 |
+| Resolution | 1024 |
+| Apply strength | 0.5 |
+
+`emmy-s5.char`, trained on RAW:
+
 | | |
 | --- | --- |
 | Base | `krea2_raw_bf16.safetensors` (Krea 2 RAW) |
@@ -69,10 +92,14 @@ the character.
 | Batch size | 1 |
 | Scope | full (attention + feed-forward) |
 | Caption dropout | 0.05 |
+| Apply strength | 1.0 |
+
+The RAW file came first, and training on RAW was deliberate: Turbo is step-distilled, and an
+adapter trained on RAW loads onto Turbo afterwards anyway. The Turbo file tests that directly by
+training on Turbo itself, at 1024 rather than 512, and applying at half strength.
 
-Trained on RAW rather than Turbo on purpose. Turbo is step-distilled and trains badly; the adapter
-still loads on Turbo afterwards, which is faster and usually better. Every training image used the
-description above as its caption, so `emmy4k` is what the adapter binds to.
+Every training image used the description above as its caption in both runs, so `emmy4k` is what
+each adapter binds to.
 
 The 500-step checkpoint beat the 800-step one on the same references. With five images that is 100
 passes each, and past roughly that point the adapter starts returning the training frames instead
@@ -94,8 +121,10 @@ walking on a forest trail, half body shot
 Not the description again. It is already there, and repeating it pushes the adapter harder toward
 the frames it trained on.
 
-For Krea 2, generate with **Krea 2 Turbo** at 8 steps and guidance 0. The adapter trained against
-RAW and loads onto Turbo as intended.
+For Krea 2, generate with **Krea 2 Turbo** at 8 steps and guidance 0, whichever file you use. The
+RAW-trained adapter loads onto Turbo as intended, and the Turbo-trained one was built against it.
+Each file carries its own apply strength, 1.0 for the RAW one and 0.5 for the Turbo one, so leave
+the strength alone unless you are deliberately dialling the identity up or down.
 
 ## Building your own