Update README.md

README.md

@@ -14,36 +14,35 @@ tags:
 ![TransMind Logo](https://file.cdn.shimoko.com/trrr.png)  
 
 
-**TransMind** 是基于先进大语言模型架构的通信领域专家模型，专为通信行业优化设计。本模型在强大的 QwQ-32B 基础架构上，通过领域特定的强化学习训练，实现了通信知识的深度融合与专业能力增强。这是一款拥有 320 亿参数的模型，其性能可与具备 6710 亿参数（其中 370 亿被激活）的 DeepSeek-R1 媲美。
+**TransMind** is an expert AI model for the communications domain, built on an advanced large language model architecture and specifically optimized for the telecommunications industry. Developed on the robust QwQ-32B foundation, this model achieves deep integration of communication knowledge and enhanced professional capabilities through domain-specific reinforcement learning. With 32 billion parameters, its performance rivals DeepSeek-R1 (which utilizes 67.1B parameters, 37B activated).
 
-## 模型亮点
+## Key Features
 
+### 🚀 Expert-Level Communication Capabilities
+Mastery of communication protocols (5G/6G, TCP/IP, HTTP/3); Profound understanding of wireless communication principles & signal processing; Network optimization & fault diagnosis expertise; Communication system design & planning proficiency; Professional interpretation of telecom standards & specifications
 
-### 🚀 通信领域专家级能力
-精通通信协议（5G/6G, TCP/IP, HTTP/3等）；深入理解无线通信原理与信号处理；网络优化与故障诊断专家；通信系统设计与规划能力；电信标准与规范专业解读
+### ⚡ Reinforcement Learning Enhanced Architecture
+Powerful 32B-parameter foundation based on QwQ-32B; Optimized communication-domain reasoning via large-scale RL; Multi-phase training integrating specialized communication data; Deep reasoning for complex communication problem-solving; Domain-specific reward functions (Technical accuracy/Solution feasibility/Efficiency optimization/Innovation); Adaptive learning with dynamic strategy adjustment
 
-### ⚡ 强化学习增强架构
-基于QwQ-32B的320亿参数强大基础；通过大规模强化学习优化通信领域推理能力；多阶段训练融合通信专业数据；实现复杂通信问题深度推理与解决；采用通信场景专用奖励函数（技术准确性/解决方案可行性/效率优化/创新性）；自适应学习机制动态调整策略
+### 🛠️ Intelligent Agent Capabilities
+Integrated communication-specific tool support; Dynamic solution adjustment based on network feedback; End-to-end system analysis & optimization; Multi-step technical diagnosis & troubleshooting; Real-time performance monitoring & feedback loops
 
-### 🛠️ 智能代理能力
-支持通信专用工具集成与调用；根据网络环境反馈动态调整解决方案；端到端通信系统分析与优化；多步骤技术问题诊断与处理；实时性能监控与反馈循环
-
-## 技术优势
+## Technical Advantages
 
 ```mermaid
 graph LR
-A[QwQ-32B基础架构] --> B[通信领域强化学习]
-B --> C[通信协议专家]
-B --> D[网络优化引擎]
-B --> E[系统设计能力]
+A[QwQ-32B Base Architecture] --> B[Communication-Domain RL]
+B --> C[Protocol Expertise]
+B --> D[Network Optimization Engine]
+B --> E[System Design Capabilities]
 C --> F[TransMind]
 ````
 
 
-## 快速使用
+## Quick Start
 
-这里提供了一个带有 apply_chat_template 的代码示例，向您展示如何加载标记器和模型以及如何生成内容。
-`````
+Example using apply_chat_template to load tokenizer/model and generate content:
+`````python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 model_name = "Qwen/QwQ-32B"
@@ -80,26 +79,14 @@ print(response)
 
 ``````
 
-## 贡献与许可
-我们欢迎通信领域专家参与模型优化！请通过以下方式贡献：
-- 提交通信领域专业数据集
-- 报告领域特定问题和优化通信工具集成
-
-
-许可证：Apache License 2.0
-
-SDK下载
-```bash
-#安装ModelScope
-pip install modelscope
-```
-```python
-#SDK模型下载
-from modelscope import snapshot_download
-model_dir = snapshot_download('hanoch1/TransMind')
-```
-Git下载
-```
-#Git模型下载
-git clone https://www.modelscope.cn/hanoch1/TransMind.git
-```
+## Contribution & Licensing
+We welcome communication domain experts to participate in model optimization! Contribute through:
+
+Submitting specialized communication datasets
+
+Reporting domain-specific issues
+
+Optimizing communication tool integrations
+
+License: Apache License 2.0
+