ZhangQiao123
/

MedGemma3N-chinese-qa-v1

@@ -1,210 +1,122 @@
 ---
-base_model: unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit
-library_name: peft
-pipeline_tag: text-generation
 tags:
-- base_model:adapter:unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit
 - lora
-- sft
-- transformers
-- trl
 - unsloth
 ---
-# Model Card for Model ID
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-### Framework versions
-- PEFT 0.16.0

 ---
+language:
+- zh
+license: apache-2.0
+library_name: transformers
 tags:
+- medical
+- chinese
+- qa
+- gemma3n
 - lora
 - unsloth
+base_model: unsloth/gemma-3n-E4B-it
+datasets:
+- FreedomIntelligence/huatuo_encyclopedia_qa
+- FreedomIntelligence/medical-o1-reasoning-SFT
+- FreedomIntelligence/huatuo_knowledge_graph_qa
+pipeline_tag: text-generation
 ---
+# MedGemma3N-chinese-qa-v1
+## 模型简介
+MedGemma3N-chinese-qa-v1 是基于 Gemma3N-4B 架构的中文医学问答模型第一阶段版本，专门针对中文医学领域进行了微调优化。
+## 模型特点
+- **版本**: v1 (第一阶段基础版本)
+- **基础架构**: Gemma3N-4B + LoRA微调
+- **训练数据**: 13,153条高质量中文医学问答数据
+- **数据扩展**: 相比原始数据增长4.7倍
+- **专业领域**: 涵盖疾病诊断、治疗建议、药物咨询等
+- **后续计划**: 将基于85,000条专业临床数据进行第二阶段增强
+## 训练数据来源
+| 数据源 | 数量 | 占比 | 描述 |
+|--------|------|------|------|
+| 华佗百科问答 | 7,960条 | 60.5% | 复旦大学华佗医学百科问答数据集 |
+| 医疗推理数据 | 2,924条 | 22.2% | FreedomIntelligence医学O1推理数据 |
+| 华佗知识图谱 | 2,269条 | 17.3% | 结构化医学知识问答数据 |
+## 训练配置
+- **基础模型**: unsloth/gemma-3n-E4B-it
+- **微调方法**: LoRA (rank=16, alpha=32)
+- **训练步数**: 8,000步
+- **学习率**: 2e-4
+- **批次大小**: 4 (1×4梯度累积)
+- **优化器**: adamw_8bit
+## 使用方法
+```python
+from unsloth import FastModel
+# 加载模型
+model, tokenizer = FastModel.from_pretrained(
+    "ZhangQiao123/MedGemma3N-chinese-qa-v1",
+    dtype=None,
+    load_in_4bit=True
+)
+# 生成回答
+messages = [{"role": "user", "content": "什么是高血压？"}]
+inputs = tokenizer.apply_chat_template(messages, tokenize=True, return_tensors="pt")
+outputs = model.generate(
+    inputs,
+    max_new_tokens=512,
+    temperature=0.7,
+    do_sample=True
+)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+## 应用场景
+- 中文医学问答
+- 疾病症状咨询
+- 治疗建议提供
+- 药物使用指导
+- 医学知识解释
+## 模型性能
+该模型在以下方面表现优秀：
+- ✅ 医学术语理解准确
+- ✅ 疾病诊断推理合理
+- ✅ 治疗建议专业可靠
+- ✅ 中文医学表达流畅
+## 注意事项
+⚠️ **重要提醒**:
+- 本模型仅供学习研究使用
+- 不能替代专业医生诊断
+- 实际医疗决策请咨询专业医生
+- 模型回答仅供参考
+## 技术细节
+- **模型大小**: ~4B参数 + LoRA适配器
+- **推理速度**: 支持4位量化快速推理
+- **内存需求**: 约8-12GB GPU内存
+- **支持框架**: Transformers, Unsloth
+## 开发团队
+基于Unsloth框架和FreedomIntelligence数据集开发
+## 许可证
+Apache 2.0
+## 更新日志
+- **v1.0** (2025-01-25): 第一阶段基础版本发布，基于13,153条中文医学数据训练
+- **计划v2.0**: 第二阶段专业增强版本，将基于85,000条专业临床数据进行训练