Introduction of refcontrol-FLUX.2-klein-9B-reference-pose-lora
Model Details of refcontrol-FLUX.2-klein-9B-reference-pose-lora
RefControl FLUX.2 Klein 9B โ Reference Pose LoRA
๐ Short description
A LoRA for
FLUX.2 Klein 9B Base
that fuses a
reference image
(identity) with a
pose control map
(skeleton / keypoints).
It preserves
identity and style
from the reference while following the
body pose and structure
from the pose map.
Trigger phrase:
apply pose from image 1 with reference from image 2
๐ Examples
Each preview is a
single combined image
from ComfyUI:
Pose โ Reference โ Result
(left to right).
Pose โ Reference โ Result
---
๐ Extended description
This LoRA was primarily trained on
humans
, but it also works with
stylized characters
and some objects.
Its main purpose is to
preserve identity
โ facial features, hairstyle, clothing, or object details โ from the reference image, while adapting the subject to the
pose and skeleton structure
defined by the control map.
FLUX.2 Klein 9B Base
already handles reference + pose transfer reasonably well with the right prompt alone. This LoRA builds on that capability โ it improves consistency and
better preserves character identity and pose fidelity
than the base model without LoRA.
Part of the
RefControl
family: reference + control fusion for consistent, controllable generation on
FLUX.2 Klein 9B Base
.
โ๏ธ How to use
Use the
first image
as the
pose control map
(skeleton / keypoints).
Use the
second image
as the
reference
(character, person, or object).
Add the trigger phrase
apply pose from image 1 with reference from image 2
in your prompt.
Adjust LoRA weight (recommended
0.8โ1.0
) depending on how strongly you want to preserve identity.
Trained on and recommended with
black-forest-labs/FLUX.2-klein-base-9B
.
The undistilled Base variant is intended for LoRA training and custom pipelines (~50 inference steps,
guidance_scale
~4.0).
The LoRA also works with the
4-step distilled
black-forest-labs/FLUX.2-klein-9B
for faster inference (~4 steps,
guidance_scale
~1.0), but
quality may be slightly lower
โ especially for identity and pose fidelity โ compared to the Base model.
โ Example prompt
apply pose from image 1 with reference from image 2
๐ฏ What it does
Preserves
character or object identity
across generations.
Adapts the subject to a
new pose or action
defined by the skeleton map.
Works best when the pose map has
similar proportions and scale
to the reference.
โก Tips
Best results when the pose map is not drastically different in body scale or framing from the reference.
Combine with
text prompts
to refine background, lighting, or mood.
DWPose
skeleton maps on a
black background
work well as control input.
๐ Use cases
Character posing for illustrations, comics, or storyboards.
Consistent
character design
across different poses.
Re-posing stylized characters while keeping their identity.
Creating animation keyframes from static references.
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