Update README.md

README.md

@@ -39,8 +39,9 @@
 
 The original intention behind the design of ACE++ was to unify reference image generation, local editing, 
 and controllable generation into a single framework, and to enable one model to adapt to a wider range of tasks. 
-A more versatile model is often capable of handling more complex tasks. "We have released three LoRA models for 
-specific vertical domains and a more versatile FFT model. Users can flexibly utilize these models and their 
+A more versatile model is often capable of handling more complex tasks. We have released three LoRA models for 
+specific vertical domains and a more versatile FFT model (the performance of the FFT model may decline compared 
+to the LoRA model across various tasks). Users can flexibly utilize these models and their 
 combinations for their own scenarios. Furthermore, many community members have found that using them 
 in conjunction with Redux modules significantly improves performance. We believe there are many more 
 use cases to explore.
@@ -63,6 +64,7 @@ The primary issue is the high degree of heterogeneity between the training datas
 which results in highly unstable training. Moreover, FLUX-Dev is a distilled model, and the influence of its original negative prompts on its final performance is uncertain.
 As a result, subsequent efforts will be focused on post-training the ACE model using the Wan series of foundational models.
 
+
 - I would like to emphasize that, due to the reasons mentioned earlier, the performance of the FFT model may decline compared 
 to the LoRA model across various tasks. Therefore, we recommend continuing to use the LoRA model to achieve better results. 
 We provide the FFT model with the hope that it may facilitate academic exploration and research in this area.