Update README.md

README.md

@@ -35,7 +35,7 @@ We hope to contribute to the better development of open-source artificial intell
 0. It is not recommended to train with the entire dataset all at once.
 1. It is suggested to adjust the proportions and repetition frequencies of different subcategories within the dataset according to the style of the model you wish to learn (this can be done by directly adding or deleting data).
 2. You can check if the current prompt is what you want, and if not, write Python scripts to perform batch replacements (you can even use models like GPT4-V, Qwen-VL, BLIP2, Deepbooru, etc., to replace the current tags as needed).
-3. For the categories you're particularly interested in, you can manually review the specific image content and actively delete some of the poorly generated samples before training (this is akin to a manual preference selection, which will improve the final quality of the model).
+3. For the categories you're particularly interested in, you can manually review the specific image content and actively delete some of the poorly generated samples before training (this is akin to a human preference selection, which will improve the final quality of the model).
 
 ## Download Method
 
@@ -58,7 +58,7 @@ novelai3的文本生成图片蒸馏数据集 ，包含30余G二次元动漫方
 0、不建议直接使用全部数据一股脑进行训练。   
 1、建议根据自己想要学出的模型风格，按需调整数据集中各个子类别的占比、重复次数等（可以通过直接增删数据）   
 2、可以查看当前的prompt是否是你想要的，如果不是可以编写python脚本规则进行批量替换（甚至可以调用GPT4-V、Qwen-VL、BLIP2、Deepbooru等模型按需替换掉当前标签）  
-3、针对你重点关注的那些类别，可以手动查看具体图像内容，主动删一些生成效果不好的学习样本再训练 （相当于人为偏好选择，会提升模型最终的质量表现） 
+3、针对你重点关注的那些类别，可以手动查看具体图像内容，主动删一些生成效果不好的学习样本再训练 （相当于人类偏好选择，会提升模型最终的质量表现） 
 
 ## 下载方式