Update README.md

README.md

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 license: apache-2.0
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-# S1-Base: 磐石科学基础大模型  
+---  
    
-## 模型介绍  
-
-磐石科学基础大模型（S1-Base），它采用专业科学知识和数据进行训练，是服务于科学任务的通专融合的科学领域多模态大模型，应用于科学推理场景与复杂学科任务。该模型现阶段采用异构混合专家架构，能够根据用户问题自动“路由”至深度定制的语言大模型或领域专用模型（波、谱、场、蛋白质、生物序列等）。
-
-本仓库为 S1-Base 系列中的通用科学大语言模型，它系统地学习并理解 “数理化天地生” 六大基础学科核心理论、定律与专业知识，依托 1.7 亿篇科研论文，在数百万条高质量科学推理数据上经过科学指令微调和多学科复合奖励强化学习训练得到，并通过高中、本科及硕博课程式训练策略逐步强化其学科能力。
-
-该模型共有三个参数量级，分别是 S1-Base-8B，S1-Base-32B 和 S1-Base-671B，其中 S1-Base-8B 和 S1-Base-32B 分别基于 [Qwen3-8B](https://github.com/QwenLM/Qwen3) 和 [Qwen3-32B](https://github.com/QwenLM/Qwen3) 训练得到，S1-Base-671B 基于 [DeepSeek-R1-671B](https://github.com/deepseek-ai/DeepSeek-R1) 训练得到，均支持 32k 上下文。      
-
+# S1-Base: Scientific Foundation Model  
    
-## 模型权重  
+[中文版](./README_zh.md) ｜ [English](./README.md)
 
-S1-Base 模型以 Apache 2.0 协议开源，您可以在 [Huggingface](https://huggingface.co/collections/ScienceOne-AI/s1-base-687a2373fde4791bc6c761f0) 或 [ModelScope](https://modelscope.cn/collections/S1-Base-66b70cf6e51c48) 下载模型权重。
+## Model Introduction  
    
-| 模型名称     | Huggingface地址      | ModelScope地址          |  
-|-------------|-------------------------------------|-------------------------------------|  
-|S1-Base-8B   | [S1-Base-8B](https://huggingface.co/ScienceOne-AI/S1-Base-8B) | [S1-Base-8B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-8B) |  
-|S1-Base-32B  | [S1-Base-32B](https://huggingface.co/ScienceOne-AI/S1-Base-32B) | [S1-Base-32B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-32B) |  
-|S1-Base-671B | [S1-Base-671B](https://huggingface.co/ScienceOne-AI/S1-Base-671B) | [S1-Base-671B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-671B) |  
-
-
-## 部署方式
+The S1-Base Scientific Foundation Model is trained using professional scientific knowledge and data, serving as a general-purpose and specialized multimodal model for scientific tasks. It is designed for scientific reasoning scenarios and complex disciplinary tasks. At the current stage, the model adopts a heterogeneous Mixture-of-Experts (MoE) architecture, which can automatically “route” user queries to deeply customized large language models or domain-specific models (such as wave, spectrum, field, protein, and biological sequence models).  
+   
+This repository provides the general scientific large language model from the S1-Base series. The model systematically learns and understands the core theories, laws, and specialized knowledge of the six major foundational disciplines: mathematics, physics, chemistry, earth science, astronomy, and biology. It is trained on 170 million scientific papers and fine-tuned with millions of high-quality scientific reasoning data through scientific instruction tuning and multi-disciplinary composite reinforcement learning. The model’s subject capabilities are further strengthened step-by-step using training strategies based on high school, undergraduate, and graduate-level curricula.  
+   
+There are three parameter sizes available for this model: S1-Base-8B, S1-Base-32B, and S1-Base-671B. S1-Base-8B and S1-Base-32B are trained based on [Qwen3-8B](https://github.com/QwenLM/Qwen3) and [Qwen3-32B](https://github.com/QwenLM/Qwen3), respectively, while S1-Base-671B is trained based on [DeepSeek-R1-671B](https://github.com/deepseek-ai/DeepSeek-R1). All versions support a 32k context window.  
+   
+## Model Weights  
+   
+S1-Base is open-sourced under the Apache 2.0 license. You can download the model weights from [Huggingface](https://huggingface.co/collections/ScienceOne-AI/s1-base-687a2373fde4791bc6c761f0) or [ModelScope](https://modelscope.cn/collections/S1-Base-66b70cf6e51c48).  
+   
+| Model Name     | Huggingface Link     | ModelScope Link         |  
+|----------------|----------------------|-------------------------|  
+| S1-Base-8B     | [S1-Base-8B](https://huggingface.co/ScienceOne-AI/S1-Base-8B) | [S1-Base-8B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-8B) |  
+| S1-Base-32B    | [S1-Base-32B](https://huggingface.co/ScienceOne-AI/S1-Base-32B) | [S1-Base-32B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-32B) |  
+| S1-Base-671B   | [S1-Base-671B](https://huggingface.co/ScienceOne-AI/S1-Base-671B) | [S1-Base-671B](https://modelscope.cn/models/ScienceOne-AI/S1-Base-671B) |  
+   
+## Deployment  
    
-我们推荐使用 [vLLM](https://github.com/vllm-project/vllm) 部署 S1-Base，实现高效推理与 OpenAI 兼容的 API 服务。  
+We recommend using [vLLM](https://github.com/vllm-project/vllm) to deploy S1-Base for efficient inference and OpenAI-compatible API services.  
    
-**快速启动命令示例：**  
+**Quick start command example:**  
 ```bash  
 pip install vllm  
-vllm serve <your_s1_model_path> --served-model-name S1-Base-671B
+vllm serve <your_s1_model_path> --served-model-name S1-Base-671B  
 ```  
-API 请求和响应格式与 OpenAI 基本一致，详细可参考 vLLM 官方文档。  
+The API request and response formats are basically consistent with OpenAI. Please refer to the official vLLM documentation for details.