Update README.md

README.md

@@ -53,14 +53,15 @@ We propose **OneReward**, a novel RLHF methodology for the visual domain by empl
 pip install -U diffusers
 ```
 
-The following contains a code snippet illustrating how to use the model to generate images based on text prompts and input mask, support inpaint(image-fill), outpaint(image-extend), eraser(object-removal). As the model is fully trained, FluxFillCFGPipeline with cfg is needed.
+The following contains a code snippet illustrating how to use the model to generate images based on text prompts and input mask, support inpaint(image-fill), outpaint(image-extend), eraser(object-removal). As the model is fully trained, FluxFillCFGPipeline with cfg is needed, you can find it in our github.
 
 ```python
 import torch
-from src.pipeline_flux_fill_with_cfg import FluxFillCFGPipeline
 from diffusers.utils import load_image
 from diffusers import FluxTransformer2DModel
 
+from src.pipeline_flux_fill_with_cfg import FluxFillCFGPipeline
+
 transformer_onereward = FluxTransformer2DModel.from_pretrained(
     "bytedance-research/OneReward",
     subfolder="flux.1-fill-dev-OneReward-transformer",
@@ -103,6 +104,7 @@ image.save(f"image_fill.jpg")
   </tr>
 </table>
 
+
 ## Model
 ### FLUX.1-Fill-dev[OneReward], trained with Alg.1 in paper
 ```python