Update README.md

README.md

@@ -32,7 +32,7 @@ In terms of performance, the hybrid linear model is comparable in overall perfor
 
 ## Evaluation
 
-To better demonstrate our model's reasoning capabilities, we compared it with three other models—Ring-mini-2.0, Qwen3-8B-thinking, and GPT-OSS-20B-Medium—on 5 challenging reasoning benchmarks across mathematics, code, and science. We observe that the mixed-linear architecture achieves performance comparable to that of softmax attention.
+To better demonstrate our model's reasoning capabilities, we compared it with three other models—Ring-mini-2.0, Qwen3-8B-thinking, and GPT-OSS-20B-Medium—on 5 challenging reasoning benchmarks across mathematics, code, and science. We observe that the hybrid-linear architecture achieves performance comparable to that of softmax attention.
 
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@@ -68,7 +68,7 @@ The results are remarkable. In the prefill stage, Ring-mini-linear-2.0's perform
 
 |     **Model**      | **#Total Params** | **#Activated Params** | **Context Length** | **Download** |
 | :----------------: | :---------------: | :-------------------: | :----------------: | :----------: |
-| Ring-mini-linear-2.0 |       16.8B       |         1.4B         |        128K         |      [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ring-mini-linear-2.0) <br>[🤖 Modelscope](https://modelscope.cn/models/inclusionAI/Ring-mini-linear-2.0)|
+| Ring-mini-linear-2.0 |       16B       |         1.4B         |        128K         |      [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ring-mini-linear-2.0) <br>[🤖 Modelscope](https://modelscope.cn/models/inclusionAI/Ring-mini-linear-2.0)|
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 ## Quickstart