From 1e8806a017f32369e7adea00e802c2ed11d37ce0 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 25 Aug 2026 01:01:17 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: sds-ai/Yee-R1-mini-GGUF Source: Original Platform --- .gitattributes | 56 +++++++++++++++ README.md | 131 ++++++++++++++++++++++++++++++++++ Yee-R1-mini-BF16.gguf | 3 + Yee-R1-mini-F16.gguf | 3 + Yee-R1-mini-IQ3_M-imat.gguf | 3 + Yee-R1-mini-IQ3_S-imat.gguf | 3 + Yee-R1-mini-IQ3_XS-imat.gguf | 3 + Yee-R1-mini-IQ3_XXS-imat.gguf | 3 + Yee-R1-mini-IQ4_NL-imat.gguf | 3 + Yee-R1-mini-IQ4_XS-imat.gguf | 3 + Yee-R1-mini-Q2_K-imat.gguf | 3 + Yee-R1-mini-Q2_K_S-imat.gguf | 3 + Yee-R1-mini-Q3_K_L-imat.gguf | 3 + Yee-R1-mini-Q3_K_M-imat.gguf | 3 + Yee-R1-mini-Q3_K_S-imat.gguf | 3 + 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数据安全专家大模型** 为核心技术基座，构建了全栈式数据安全审计与全链路防泄露体系，在“云”、“管”、“端”三大场景中落地应用，助力企业从容应对数字经济时代的安全挑战。 + +--- + +## 🔍 核心特点 + +- **基于 Qwen3-1.7B 构建** + - 使用阿里巴巴通义千问最新一代大语言模型 Qwen3，具备强大的推理、逻辑判断与指令执行能力。 + - 支持在 **Thinking Mode** 和 **Non-Thinking Mode** 之间灵活切换，适应不同应用场景。 + +- **双模推理机制** + - 在复杂逻辑任务（如代码分析、数学计算、策略制定）中启用 Thinking Mode。 + - 在日常对话、快速响应场景中使用 Non-Thinking Mode，提升效率。 + +- **Agent 化能力** + - 集成 Qwen-Agent 框架，支持调用外部工具（如数据库接口、日志分析器、API 接口等），实现自动化任务执行。 + +- **高兼容性** + - 支持主流部署方式：本地运行、Docker 容器、Kubernetes 集群、SaaS API 接口等。 + - 兼容 HuggingFace Transformers、vLLM、SGLang、Ollama 等推理框架。 + +--- + +## 📊 性能测试 + +以下是小熠在 [CS-Eval](https://cs-eval.com/#/app/leaderBoard) 中多个安全领域的综合得分测试结果，基于模拟真实业务场景的评估体系生成： + +| 综合得分 | 系统安全及软件安全基础 | 访问控制与身份管理 | 加密技术与密钥管理 | 基础设施安全 | AI与网络安全 | 漏洞管理与渗透测试 | 威胁检测与预防 | 数据安全和隐私保护 | 供应链安全 | 安全架构设计 | 业务连续性与应急响应恢复 | 中文任务 | 英文任务 | +|----------|------------------------|--------------------|--------------------|--------------|--------------|--------------------|----------------|--------------------|------------|--------------|--------------------------|----------|----------| +| 77.48 | 78.00 | 79.31 | 71.90 | 78.37 | 84.65 | 75.24 | 78.41 | 73.02 | 86.71 | 80.49 | 71.33 | 77.58 | 76.03 | + +--- + +## 📦 快速开始 + +```python +from transformers import AutoTokenizer, AutoModelForCausalLM + +# 加载 tokenizer 和模型 +tokenizer = AutoTokenizer.from_pretrained("sds-ai/Yee-R1-mini") +model = AutoModelForCausalLM.from_pretrained( + "sds-ai/Yee-R1-mini", + torch_dtype="auto", + device_map="auto" +) + +# 输入提示 +prompt = "请帮我检查这份数据是否包含敏感字段？" + +# 应用聊天模板并切换模式 +messages = [{"role": "user", "content": prompt}] +text = tokenizer.apply_chat_template( + messages, + tokenize=False, + add_generation_prompt=True, + enable_thinking=True # 切换至思考模式 +) + +# 编码输入 +inputs = tokenizer([text], return_tensors="pt").to(model.device) + +# 生成响应 +response_ids = model.generate(**inputs, max_new_tokens=32768) +response = tokenizer.decode(response_ids[0][len(inputs.input_ids[0]):], skip_special_tokens=True) + +print("小熠：\n", response) +``` + +--- + +## 🛠️ 部署方式 + +你可以通过以下任意一种方式部署小熠： + +### 使用 SGLang 启动服务 +```bash +python -m sglang.launch_server --model-path sds-ai/Yee-R1-mini --reasoning-parser qwen3 +``` + +### 使用 vLLM 启动服务 +```bash +vllm serve sds-ai/Yee-R1-mini --enable-reasoning --reasoning-parser deepseek_r1 +``` + +### 使用 Ollama / LMStudio / llama.cpp / KTransformers +Qwen3 已被主流本地化 LLM 工具广泛支持，详情请参考官方文档。 + +--- + +## 📚 最佳实践建议 + +为获得最佳性能，请遵循以下推荐设置： + +| 场景 | 温度 | TopP | TopK | MinP | Presence Penalty | +|------|------|------|------|------|------------------| +| 思考模式 (`enable_thinking=True`) | 0.6 | 0.95 | 20 | 0 | 1.5 (减少重复输出) | +| 非思考模式 (`enable_thinking=False`) | 0.7 | 0.8 | 20 | 0 | 不推荐使用 | + +- 输出长度建议设为 **32,768 tokens**，复杂任务可提升至 **38,912 tokens**。 +- 在多轮对话中，历史记录应仅保留最终输出部分，避免引入思维内容影响上下文理解。 + + +--- + +## 📞 联系我们 + +了解更多关于小熠的信息，请访问 [熠数信息官网](https://shining-data.com) + +--- + +## 🌟 致谢 + +感谢阿里通义实验室开源 Qwen3 模型，为小熠提供了坚实的语言理解和生成能力基础。 diff --git a/Yee-R1-mini-BF16.gguf b/Yee-R1-mini-BF16.gguf new file mode 100644 index 0000000..23467a4 --- /dev/null +++ b/Yee-R1-mini-BF16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d6acc969e1fb3705fc7b86219d5ab2e1e4b83a674367c86e1d2a95d7a94f1b79 +size 3447349312 diff --git a/Yee-R1-mini-F16.gguf b/Yee-R1-mini-F16.gguf new file mode 100644 index 0000000..5936013 --- /dev/null +++ b/Yee-R1-mini-F16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3bb29e0aada5d37a32f902f5efb9aa3c1946a26d30443f2d3d922e999b0eb723 +size 3447349312 diff --git a/Yee-R1-mini-IQ3_M-imat.gguf b/Yee-R1-mini-IQ3_M-imat.gguf new file mode 100644 index 0000000..41880d8 --- /dev/null +++ b/Yee-R1-mini-IQ3_M-imat.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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