Update README.md

README.md

@@ -4,202 +4,94 @@ language:
 - zh
 base_model:
 - Qwen/Qwen3-4B-Thinking-2507
-pipeline_tag: text-classification
+pipeline_tag: text-generation
 tags:
 - datacenter
 - 数创共生
+- 数据中心
+- 电气系统
+- 暖通空调
+- 消防系统
+- 智能化系统
+- 运维管理
+- 工程设计
+- 中文模型
 ---
-# Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+# Model Card for Data Center Expert Model
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+## Model Description
 
-## Model Details
+本模型是一个面向数据中心全生命周期的专业大语言模型，基于大量真实世界的数据中心设计规划、工程建设与运行维护数据集进行训练。模型在以下专业领域具备扎实的知识与推理能力：
 
-### Model Description
+- **电气系统**：包括高低压配电、UPS、柴油发电机、PDU、能效管理等；
+- **暖通空调（HVAC）**：涵盖冷源系统、气流组织、热负荷计算、节能策略等；
+- **消防系统**：气体灭火、火灾报警、防排烟设计等规范与实践；
+- **智能化系统**：动环监控（DCIM）、楼宇自控（BAS）、安防与门禁集成等；
+- **建筑与装修**：结构承重、抗震设防、防静电地板、屏蔽与降噪等；
+- **运维管理**：故障诊断、容量规划、SLA保障、绿色低碳运营等。
 
-<!-- Provide a longer summary of what this model is. -->
+- **Developed by:** 广州数创共生人工智能化有限公司
+- **Model type:** 基于Qwen3-4B-Thinking-2507微调的大语言模型
+- **Language(s) (NLP):** 中文（针对中国及亚太地区数据中心实践优化）
+- **License:** Apache 2.0
+- **Finetuned from model:** Qwen/Qwen3-4B-Thinking-2507
 
+## Model Sources
 
-
-- **Developed by:** 广州数创共生人工智能技术有限公司
-- **Funded by [optional]:** None
-- **Shared by [optional]:** all
-- **Model type:** 数据中心专家模型
-- **Language(s) (NLP):** 中文
-- **License:** None
-- **Finetuned from model [optional]:** Qwen3-4B-Thinking-2507
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** 数据中心规划设计、工程建设、系统运维等方面技能专家，拥有数据中心相关机电、暖通、消防、智能化、装修、建筑等方面专业知识。
+- **Repository:** https://huggingface.co/your-username/data-center-expert-model
+- **Demo:** 可通过ModelScope或Hugging Face Inference API试用
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+- 数据中心咨询设计问答
+- 施工图审查与技术文档生成
+- 运维故障诊断与辅助决策
+- 数据中心技术培训问答
+- 行业规范标准解读（TIA-942、GB50174、Uptime Institute Tier等）
 
-[More Information Needed]
+### Downstream Use
 
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+- 集成至DCIM系统作为智能运维助手
+- 嵌入设计软件提供实时规范检查
+- 构建数据中心知识库问答系统
+- 开发面向特定客户的定制化咨询工具
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+- 非数据中心领域的通用问答
+- 替代专业工程师的最终决策
+- 涉及生命安全的关键系统自动控制
+- 超出训练数据时效性的最新技术规范
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- **知识时效性**：模型基于训练数据中的规范标准，可能无法反映最新修订版本
+- **地域适用性**：主要针对中国及亚太地区实践优化，其他地区应用需核实当地规范
+- **专业边界**：模型建议不能替代注册工程师的签字确认，重大决策需人工复核
+- **数据偏差**：训练数据来源于历史项目，可能存在特定厂商技术路线偏好
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+- 用户应结合最新版规范标准交叉验证模型输出
+- 关键设计参数和故障处理建议需由专业工程师审核
+- 建议明确标注AI生���内容，避免误用
+- 定期使用最新行业文档进行模型更新
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-通过多个大型数据中心的方案训练而成，包含T4级别、国标A级数据中心相关数据。
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
+```python
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
 
-## Model Card Contact
+# 加载模型推理管道
+inference_pipeline = pipeline(
+    task=Tasks.chat,
+    model='your-username/data-center-expert-model'  # 替换为你的实际模型ID
+)
 
-[More Information Needed]
+# 提问示例
+response = inference_pipeline("一个国标A级数据中心的空调冗余性设计方案设计怎么样的？")
+print(response['response'])