feat update readme

README.md

@@ -53,14 +53,14 @@ widget:
       summary brief to ru: 在北京冬奥会自由式滑雪女子坡面障碍技巧决赛中，中国选手谷爱凌夺得银牌。祝贺谷爱凌！今天上午，自由式滑雪女子坡面障碍技巧决赛举行。决赛分三轮进行，取选手最佳成绩排名决出奖牌。第一跳，中国选手谷爱凌获得69.90分。在12位选手中排名第三。完成动作后，谷爱凌又扮了个鬼脸，甚是可爱。第二轮中，谷爱凌在道具区第三个障碍处失误，落地时摔倒。获得16.98分。网友：摔倒了也没关系，继续加油！在第二跳失误摔倒的情况下，谷爱凌顶住压力，第三跳稳稳发挥，流畅落地！获得86.23分！此轮比赛，共12位选手参赛，谷爱凌第10位出场。网友：看比赛时我比谷爱凌紧张，加油！
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-# T5 model for text Summary in English, Russian and Chinese language
+# T5 model for multilingual text Summary in English, Russian and Chinese language
 
 This model is designed to perform the task of controlled generation of summary text content in multitasking mode with a built-in translation function for languages: Russian, Chinese, English.
 
 This is the T5 multitasking model. Which has a conditionally controlled ability to generate summary text content, and translate this. In total, she understands 12 commands, according to the set prefix: 
-1) "summary: " - to generate simple concise content
-2) "summary brief: " - to generate a shortened summary content
-3) "summary big: " - to generate elongated summary content
+1) "summary: " - to generate simple concise content in the source language
+2) "summary brief: " - to generate a shortened summary content in the source language
+3) "summary big: " - to generate elongated summary content in the source language
 
 The model can understand text in any language from the list: Russian, Chinese or English. It can also translate the result into any language from the list: Russian, Chinese or English.