---
license: apache-2.0
library_name: diffusers
pipeline_tag: image-to-image
base_model: LetsThink/RORem
tags:
- inpainting
- object-removal
- lcm
- sd-xl
---

# RORem (merged)

SDXL - RORem (CVPR 2025) repackaged as a plain diffusers
`StableDiffusionXLInpaintPipeline`: the [LetsThink/RORem](https://huggingface.co/LetsThink/RORem)
weights with their LCM-distillation LoRA already merged into the UNet, so
conversion pipelines install straight from this repository with no adapter
step. Nothing was retrained — the merge is a plain B@A bake at scale 1
(788 adapters), numerically equivalent to diffusers' own `fuse_lora`.

## Inference contract

Verified by instrumenting the reference `inference_RORem_4S.py` call
(diffusers 0.41):

```python
pipe(prompt="", image=image, mask_image=mask, guidance_scale=1.0,
     num_inference_steps=4, strength=0.99)  # LCMScheduler
```

The scheduler places [999, 759, 499, 259] and the strength slice drops the
head — three denoiser passes at **[759, 499, 259]**, with the photo noised
to 759. Guidance is off and the prompt is empty: RORem is prompt-free.

## Provenance

Derived from [LetsThink/RORem](https://huggingface.co/LetsThink/RORem)
(Apache-2.0), the LCM LoRA from the RORem-LCM release, on the
[CreativeML Open RAIL++-M](https://huggingface.co/diffusers/stable-diffusion-xl-1.0-inpainting-0.1)
SDXL inpainting base. Project page: github.com/leeruibin/RORem.