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README.md

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 # ​**PCL-Reasoner-V1 Model**​
 
 ## Model Overview  
-We release ​**PCL-Reasoner-V1**​， a model trained based on ​**Qwen2.5-32B-Base**​ and undergoes high-performance supervised fine-tuning based on the ​**MindSpore framework**​ and ​**Ascend hardware**. After fine-tuning, the model demonstrates significant improvements in mathematical reasoning capabilities. PCL-Reasoner-V1 achieves 85.7% and 84.2 respectively on AIME 24 and AIME 25, which position PCL-Reasoner-V1 among the top-tier models in the 32B parameter class.  
+We release ​PCL-Reasoner-V1​, a model trained based on ​Qwen2.5-32B-Base​ and undergoes high-performance supervised fine-tuning based on the ​MindSpore framework​ and ​Ascend hardware. After fine-tuning, the model demonstrates significant improvements in mathematical reasoning capabilities. PCL-Reasoner-V1 achieves 85.7% and 84.2% respectively on AIME 24 and AIME 25, which position PCL-Reasoner-V1 among the top-tier models in the 32B parameter class.
 
-To promote technical collaboration and application, we have fully open-sourced model weights, dataset and training code  
-PCL-Reasoner-V1 not only represents a leading 32B mathematical reasoning model but also provides developers with valuable expertise in domain-specific supervised fine-tuning and post-training solutions. Follow the tutorial below to deploy and explore advanced post-training methodologies!  
+We have fully open-sourced the model weights, dataset and training code. Follow the tutorial below to deploy and explore post-training!
 
 ![eval_results](images/README/eval_results.png)