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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

LICENSE

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README.md

@@ -1,3 +1,122 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- chat
+library_name: transformers
+---
+<div align="center">
+
+# Baichuan-M2-32B
+
+[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
+[![Hugging Face](https://img.shields.io/badge/🤗%20Hugging%20Face-Model-yellow)](https://huggingface.co/baichuan-inc/Baichuan-M2-32B)
+
+</div>
+
+## 🌟 模型简介
+
+Baichuan-M2-32B 是百川智能推出的医疗增强推理模型，这是百川开源发布的第二个医疗增强模型，专为真实世界的医疗推理任务设计。该模型基于 Qwen2.5-32B 基座，通过创新的大型验证器系统（Large Verifier System）从真实世界的医疗问题出发，进行医疗领域后训练对齐，在保持模型通用能力的同时，实现了医疗效果的突破性提升。
+
+**模型特点：**
+
+Baichuan-M2 采用了三个核心技术创新：首先通过**大型验证器系统**，结合医疗场景特点设计了全面的医疗验证体系，包含患者模拟器和多维度验证机制；其次通过**医疗领域适应性增强**的中期训练（Mid-Training），在保持通用能力的同时实现轻量高效的医疗领域适应；最后采用**多阶段强化学习**策略，将复杂的 RL 任务分解为层次化的训练阶段，逐步提升模型的医学常识、推理和患者交互能力。
+
+**核心亮点：**
+- 🏆 **全球最强医疗开源模型**：在 HealthBench 评测集上超越所有开源模型及众多前沿闭源模型，是最接近 GPT-5 医疗能力的开源大模型
+- 🧠 **医生思维对齐**：基于真实病例数据和患者模拟器训练，具备临床诊断思维和鲁棒的医患交互能力
+- ⚡ **高效部署与推理**：支持 4bit 量化在 RTX4090 单卡部署，MTP 版本单用户场景下 token 吞吐提升 58.5%
+
+
+
+## 📊 性能表现
+
+### HealthBench指标
+
+| 模型名称 | healthbench | healthbench-hard | healthbench-Consensus |
+|----------|-------------|------------------|-----------------------|
+| Baichuan-M2 | 60.1 | 34.7 | 91.5 |
+| gpt-oss-120b | 57.6 | 30 | 90 |
+| Qwen3-235B-A22B-Thinking-2507 | 55.2 | 25.9 | 90.6 |
+| deepseek-r1-250528 | 53.6 | 22.6 | 91.5 |
+| glm-4.5 | 47.8 | 18.7 | 85.3 |
+| kimi-k2 | 43 | 10.7 | 90.9 |
+| gpt-oss-20b | 42.5 | 10.8 | 82.6 |
+
+### 通用指标
+
+| 评测集 | Baichuan-M2-32B | Qwen3-32B |
+|--------|-----------------|-----------|
+| AIME24 | 83.4 | 81.4 |
+| AIME25 | 72.9 | 72.9 |
+| GPQA-Diamond | 61.5 | 68.4 |
+| CFBench | 77.6 | 75.7 |
+| WritingBench | 8.56 | 7.90 |
+
+*备注：AIME 和 GPQA 的 max_length 设为 64k，其他的为 32k，温度统一为 0.6。*
+
+
+## 🛠️ 技术特色
+
+### 大型验证器系统
+- **患者模拟器**：基于真实病例构建的虚拟患者系统
+- **多维度验证**：医学准确性、回答完整性、追问感知等 8 个维度
+- **动态评分**：实时生成评分标准，适应复杂临床环境
+
+### 医疗领域适应
+- **Mid-Training**：医疗知识注入的同时保持通用能力
+- **端到端强化学习**：多阶段 RL 策略优化
+- **通专兼顾**：2:2:1 配比的医疗、通用、数学数据
+
+## 🔧 快速开始
+
+### 安装使用
+
+```bash
+# 安装依赖
+pip install transformers torch vllm sglang
+
+# Transformers 使用
+from transformers import AutoTokenizer, AutoModelForCausalLM
+model = AutoModelForCausalLM.from_pretrained("baichuan-inc/Baichuan-M2-32B", trust_remote_code=True)
+
+# vLLM 使用（推荐）
+from vllm import LLM
+llm = LLM(model="baichuan-inc/Baichuan-M2-32B", trust_remote_code=True)
+
+# SGLang 使用
+python -m sglang.launch_server --model-path baichuan-inc/Baichuan-M2-32B
+```
+
+## ⚠️ 使用须知
+
+1. **医疗免责声明**：本模型仅供研究和参考，不能替代专业医疗诊断和治疗建议
+2. **适用场景**：医学教育、健康咨询、临床辅助决策等
+3. **安全使用**：建议在专业医疗人员指导下使用
+
+## 📄 许可证
+
+本项目采用 [Apache License 2.0](LICENSE) 开源协议，欢迎研究和商业使用。
+
+## 🤝 致谢
+
+- 基础模型：Qwen2.5-32B
+- 训练框架：VERL
+- 推理引擎：vLLM、SGLang
+- 量化方法：AutoRound、GPTQ、QuaRot、QQQ
+
+感谢开源社区的贡献，我们将持续回馈社区，推动医疗 AI 技术发展。
+
+## 📞 联系我们
+
+- 更多资源：[百川智能官网](https://www.baichuan-ai.com)
+
+- 技术交流：[GitHub](https://github.com/baichuan-inc)
+
+---
+
+<div align="center">
+
+**让AI助力医疗，让健康触手可及**
+
+</div>

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config.json

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+  "transformers_version": "4.51.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+}

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
+size 11422654

tokenizer_config.json

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+  "add_prefix_space": false,
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+      "content": "<|endoftext|>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "<|im_start|>",
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+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
+    },
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+      "rstrip": false,
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+    },
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+    },
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+    },
+    "151668": {
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+      "special": false
+    }
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+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
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+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set content = message.content %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in message.content %}\n                {%- set content = message.content.split('</think>')[-1].lstrip('\\n') %}\n                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if thinking_mode is defined %}\n        {%- if thinking_mode == \"on\" %}\n            {{- '<think>\\n' }}\n        {%- elif thinking_mode == \"off\" %}\n            {{- '<think>\\n\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
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+}