初始化项目，由ModelHub XC社区提供模型

Model: zpeng1989/Medical_Dialogue_Model
Source: Original Platform

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README.md

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+# 肿瘤知识问答大模型
+
+## 项目概述
+
+本项目旨在构建一个针对肿瘤知识的问答大模型，基于`qwen2.5-7B`模型作为基座模型，使用LoRA（Low-Rank Adaptation）技术进行微调。模型训练数据涵盖了基因数据、肿瘤药物、NCCN（美国国家综合癌症网络）指南、CSCO（中国临床肿瘤学会）指南等权威肿瘤学知识信息，并通过问答题目进行微调，以提升模型在肿瘤领域的问答能力。
+
+## 模型架构
+
+- **基座模型**: `qwen2.5-7B`
+- **微调方法**: LoRA（Low-Rank Adaptation）
+- **训练数据**: 
+  - 基因数据
+  - 肿瘤药物信息
+  - NCCN指南
+  - CSCO指南
+  - 肿瘤知识问答题目
+
+## 数据集
+
+### 数据来源
+1. **基因数据**: 包含与肿瘤相关的基因突变、表达谱等信息。
+2. **肿瘤药物**: 涵盖常用肿瘤药物的适应症、副作用、作用机制等。
+3. **NCCN指南**: 美国国家综合癌症网络发布的肿瘤治疗指南。
+4. **CSCO指南**: 中国临床肿瘤学会发布的肿瘤诊疗指南。
+5. **问答题目**: 基于上述数据生成的肿瘤知识问答题目，用于模型微调。
+
+### 数据预处理
+- **数据清洗**: 去除重复、不完整或无关的数据。
+- **数据标注**: 对问答题目进行标注，确保问题和答案的准确性。
+- **数据分割**: 将数据集分为训练集、验证集和测试集。
+
+## 模型训练
+
+### 微调方法
+使用LoRA技术对`qwen2.5-7B`模型进行微调。LoRA通过在预训练模型的权重矩阵中引入低秩矩阵来减少参数量，从而在保持模型性能的同时降低计算成本。
+
+### 训练步骤
+1. **加载预训练模型**: 加载`qwen2.5-7B`模型。
+2. **应用LoRA**: 在模型的关键层应用LoRA技术。
+3. **训练模型**: 使用准备好的肿瘤知识问答数据集进行微调。
+4. **验证与测试**: 在验证集和测试集上评估模型性能，调整超参数以优化结果。
+
+## 模型评估
+
+### 评估指标
+- **准确率**: 模型在问答任务中的准确率。
+- **召回率**: 模型能够正确回答的问题比例。
+- **F1分数**: 准确率和召回率的调和平均数。
+
+### 评估结果
+在测试集上的评估结果如下：
+待更新
+
+## 使用指南
+
+### 环境配置
+1. **Python版本**: 3.10+
+2. **依赖库**:
+   - `transformers`
+   - `torch`
+
+
+### 模型下载
+
+
+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('zpeng1989/Medical_Oncology_Large_Language_Model')
+```
+Git下载
+```
+#Git模型下载
+git clone https://www.modelscope.cn/zpeng1989/Medical_Oncology_Large_Language_Model.git
+```
+
+### 模型推理
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# 加载微调后的模型
+model = AutoModelForCausalLM.from_pretrained("path_to_your_model")
+tokenizer = AutoTokenizer.from_pretrained("path_to_your_model")
+
+# 输入问题
+question = "什么是NCCN指南？"
+inputs = tokenizer(question, return_tensors="pt")
+
+# 生成答案
+outputs = model.generate(**inputs)
+answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(answer)
+```
+
+## 具体案例
+
+### Case 1
+
+```
+[
+    {
+        "role": "system",
+        "content": "你是医生"
+    },
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "text",
+                "text": "安罗替尼的副作用与肝功能有何关联？"
+            }
+        ]
+    },
+    {
+        "role": "assistant",
+        "content": "安罗替尼的副作用可能与肝功能有关，包括肝酶异常等。"
+    }
+]
+```
+
+### Case 2
+
+```
+[
+    {
+        "role": "system",
+        "content": "你是医生"
+    },
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "text",
+                "text": "KDR受体的功能和作用是什么？"
+            }
+        ]
+    },
+    {
+        "role": "assistant",
+        "content": "KDR受体主要调节VEGF激活的内皮细胞功能，在内皮细胞中促进增殖、迁移，血管渗透性以及血管再生。"
+    }
+]
+```
+
+
+## 许可证
+本项目采用 [MIT 许可证](LICENSE)。
+
+## 致谢
+- 感谢 `qwen2.5-7B` 模型的开发者。
+- 感谢 NCCN 和 CSCO 提供的指南数据。
+- 感谢所有为肿瘤知识问答数据集做出贡献的研究人员。
+
+## 联系方式
+如有任何问题，请联系 [592392714@qq.com]。
+
+---
+
+**注意**: 本项目仅供学术研究使用，不构成医疗建议。
+
+
+
+
+

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+}

special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "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_config.json

@@ -0,0 +1,208 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "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|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\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    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) 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{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}