Merge 1c10c9f6771fadcd5c8fe52cbac7075527184661 into 0cf78561f1d51c84a21b2190626b21116d5c68bb

fixing a typo

README.md

@@ -32,7 +32,7 @@
 
 We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. 
 DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrated remarkable performance on reasoning.
-With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors.
+With RL, DeepSeek-R1-Zero naturally exhibited numerous powerful and interesting reasoning behaviors.
 However, DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing. To address these issues and further enhance reasoning performance,
 we introduce DeepSeek-R1, which incorporates cold-start data before RL.
 DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks. 
@@ -187,7 +187,7 @@ python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
 
 **We recommend adhering to the following configurations when utilizing the DeepSeek-R1 series models, including benchmarking, to achieve the expected performance:**
 
-1. Set the temperature within the range of 0.5-0.7 (0.6 is recommended) to prevent endless repetitions or incoherent outputs.
+1. Set the temperature between 0.5 and 0.7 (with 0.6 recommended) to prevent endless repetition or incoherent outputs.
 2. **Avoid adding a system prompt; all instructions should be contained within the user prompt.**
 3. For mathematical problems, it is advisable to include a directive in your prompt such as: "Please reason step by step, and put your final answer within \boxed{}."
 4. When evaluating model performance, it is recommended to conduct multiple tests and average the results.
@@ -257,11 +257,11 @@ When responding, please keep the following points in mind:
 This code repository and the model weights are licensed under the [MIT License](https://github.com/deepseek-ai/DeepSeek-R1/blob/main/LICENSE).
 DeepSeek-R1 series support commercial use, allow for any modifications and derivative works, including, but not limited to, distillation for training other LLMs. Please note that:
 - DeepSeek-R1-Distill-Qwen-1.5B, DeepSeek-R1-Distill-Qwen-7B, DeepSeek-R1-Distill-Qwen-14B and DeepSeek-R1-Distill-Qwen-32B are derived from [Qwen-2.5 series](https://github.com/QwenLM/Qwen2.5), which are originally licensed under [Apache 2.0 License](https://huggingface.co/Qwen/Qwen2.5-1.5B/blob/main/LICENSE), and now finetuned with 800k samples curated with DeepSeek-R1.
-- DeepSeek-R1-Distill-Llama-8B is derived from Llama3.1-8B-Base and is originally licensed under [llama3.1 license](https://huggingface.co/meta-llama/Llama-3.1-8B/blob/main/LICENSE).
+- DeepSeek-R1-Distill-Llama-8B is derived from Llama3.1-8B-Base and is originally licensed under [Llama3.1 license](https://huggingface.co/meta-llama/Llama-3.1-8B/blob/main/LICENSE).
-- DeepSeek-R1-Distill-Llama-70B is derived from Llama3.3-70B-Instruct and is originally licensed under [llama3.3 license](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/LICENSE).
+- DeepSeek-R1-Distill-Llama-70B is derived from Llama3.3-70B-Instruct and is originally licensed under [Llama3.3 license](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/LICENSE).
 
 ## 8. Citation
-```
+```bibtex
 @misc{deepseekai2025deepseekr1incentivizingreasoningcapability,
       title={DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning}, 
       author={DeepSeek-AI},
@@ -274,4 +274,4 @@ DeepSeek-R1 series support commercial use, allow for any modifications and deriv
 ```
 
 ## 9. Contact
-If you have any questions, please raise an issue or contact us at [service@deepseek.com](service@deepseek.com).
+If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com).