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README.md

@@ -57,7 +57,7 @@ Qwen-14b-chat-yarn-32k经过微调后，在多文档问答（或检索）任务
 
 # "大海捞针"测试结果
 ![](大海捞针50k.png)
-* 可以发现即使在50k长度下(即使训练样本不大于32k)，检索信息的准确率依然极高，证明此模型确实拥有强大的长上下文能力，极大缓解“lost in the middle”问题，并且拥有极大的扩展潜力。
+* 可以发现即使在**50k**长度下(即使训练样本不大于32k)，检索信息的准确率依然极高，证明此模型确实拥有强大的长上下文能力，极大缓解“lost in the middle”问题，并且拥有极大的扩展潜力。
 * 而且此模型在推理时，不需要进行"原文复述"，只需要给出问题，并让模型直接回答问题，模型就能给出正确的答案。（相对的，claude2.1-200k 需要特定的 prompt才能正确回答）这也证明了此模型的强大能力。
 
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README_en.md

@@ -56,7 +56,7 @@ Qwen-14b-chat-yarn-32k has shown significant improvement in multi-document quest
 
 # Test Results for "Needle in a Haystack"
 ![](大海捞针50k.png)
-* The model can accurately retrieve the needle in a haystack even when the context length is 50k or longer, proving that the model does have strong long-context capabilities, which greatly alleviates the "lost in the middle" problem.
+* The model can accurately retrieve the needle in a haystack even when the context length is **50k** or longer, proving that the model does have strong long-context capabilities, which greatly alleviates the "lost in the middle" problem.
 * In addition, the model does not need to paraphrase the original text during inference, it only needs to give the question and let the model answer the question directly, and the model can give the correct answer. (In contrast, claude2.1-200k needs a specific prompt to answer correctly) This also proves the powerful ability of this model.