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GancaoDoctorAI/TraceMed
TraceMed is a text generation model from GancaoDoctorAI. Use it when you need the model to write or continue text. It is set up for transformers.
TraceMed 是采用 Qwen3 架构的文本生成模型。本仓库提供训练后的模型权重、配置、分词器和聊天模板,可通过 Hugging Face Transformers 加载使用。
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From the Hugging Face model README
TraceMed 是采用 Qwen3 架构的文本生成模型。本仓库提供训练后的模型权重、配置、分词器和聊天模板,可通过 Hugging Face Transformers 加载使用。
| 项目 | 内容 |
|---|---|
| 模型架构 | Qwen3ForCausalLM |
| 权重精度 | BF16 |
| 权重格式 | Safetensors |
| 配置上下文长度 | 32,768 tokens |
| 仓库 | GancaoDoctorAI/TraceMed |
以下截图来自我们的内部对话测试界面,左栏为 TraceMed,右栏为同尺寸基座模型 Qwen3-4B(开启思考模式),输入完全相同。回答中的角标(如 [1])可点击,直接定位到被引用的原文段落。
The screenshots below are taken from our internal chat-testing UI. The left pane is TraceMed; the right pane is the same-size base model Qwen3-4B (thinking mode on), given the identical input. Superscript markers (e.g. [1]) in our model's answers are clickable and jump to the exact source passage being cited.
主要能力 / Key capabilities
| 中文 | English |
|---|---|
| 中医辨证论治:由症状推导证型、病机、治法与方药 | TCM pattern differentiation: from symptoms to pattern, pathogenesis, treatment principle and formula |
| 有据可查:回答逐句标注引用,可溯源到教材原文 | Grounded answers: sentence-level citations traceable to textbook source passages |
| 方剂 / 概念对比:从组成、功效、适应证多维度比较 | Comparative analysis of formulas and concepts (composition, function, indications) |
| 医学考试选择题:给出答案并附带引用的解析 | Medical exam MCQs: answer plus a cited rationale |

输入 / Input
患者身热不扬,午后热甚,头痛恶寒,身重疼痛,胸闷不饥,舌白不渴,脉弦细而濡。请辨证并给出治法和代表方,引用医学依据。
A patient presents with a low-grade fever that does not feel hot to the touch and worsens in the afternoon, headache with aversion to cold, a heavy and aching body, chest oppression with no appetite, a white tongue coating without thirst, and a wiry, thin, soggy pulse. Please identify the pattern, give the treatment principle and a representative formula, and cite medical evidence.
输出(节选)/ Output (excerpt)
辨证分析
根据患者临床表现,辨证为湿温病,证属湿重于热(或湿温初起,邪遏卫气,湿重于热)。
1. 症状辨析:
· 身热不扬,午后热甚:湿性黏滞,遏阻热邪,故身热不扬;午后阳气渐衰,湿邪得阴助而势张,故午后热势加重[1][2]。
· 头痛恶寒,身重疼痛:湿邪郁遏卫阳,清阳不升,故头痛;湿性重浊,阻滞经络,故身重疼痛[3][4]。
· 胸闷不饥,舌白不渴:湿阻中焦,气机不畅,故胸闷不饥;湿邪内蕴,未化燥伤津,故舌苔白腻、口不渴[5][6]。
2. 病机概要:
本病病机为湿邪偏盛,热邪被湿所裹而不得外达,湿遏热伏,困阻中焦,气机不畅[8][9]。病位主要在上焦及中焦,涉及卫分与气分[10][11]。
……(以下略)
Pattern Analysis
Based on the clinical presentation, this is damp-warmth disease with dampness predominating over heat (early-stage damp-warmth, pathogen obstructing the defensive and qi levels).
1. Symptom analysis:
· Low-grade fever worse in the afternoon: dampness is sticky and traps heat, so the fever does not surface; in the afternoon yang qi declines and dampness, aided by yin, intensifies, so the fever worsens [1][2].
· Headache, aversion to cold, heavy aching body: dampness constrains defensive yang so clear yang cannot ascend, causing headache; dampness is heavy and turbid, obstructing the channels, causing heaviness and pain [3][4].
· Chest oppression, no appetite, white coating, no thirst: dampness obstructs the middle burner and impedes qi movement; dampness has not yet transformed into dryness to damage fluids, hence the white greasy coating and absence of thirst [5][6].
2. Pathogenesis:
Dampness predominates and envelops heat so it cannot vent outward; heat is hidden beneath dampness, obstructing the middle burner and qi movement [8][9]. The disease is located mainly in the upper and middle burners, involving the defensive and qi levels [10][11].
… (truncated)

输入 / Input
麻黄汤与桂枝汤在组成、功效、适应证上有何异同?
What are the similarities and differences between Mahuang Decoction and Guizhi Decoction in composition, function and indications?
输出(节选)/ Output (excerpt)
麻黄汤与桂枝汤均含有桂枝和甘草,体现了方剂组方中"药对"的基础作用[1]。两者在配伍法度上均遵循阴阳相对的原则,如桂枝配麻黄、桂枝配芍药等,体现了严谨的组方逻辑[2]。
在功效方面,麻黄汤具有辛温发汗、宣肺平喘的功效[3][4]。桂枝汤则具有辛温解肌、调和营卫的功效[5][6][7][8][9]。麻黄汤与桂枝汤的共同功效包括解表祛邪、调和营卫、宣通经脉[10]。……
在适应证上,两者存在显著差异。麻黄汤与桂枝汤均具有辛温解表的功效,但麻黄汤发汗力较强,适用于表实无汗证……
Both Mahuang Decoction and Guizhi Decoction contain Guizhi (cinnamon twig) and Gancao (licorice), reflecting the foundational role of herb pairs in formula construction [1]. Both follow the principle of complementary yin–yang pairing, e.g. Guizhi with Mahuang and Guizhi with Baishao, showing rigorous compositional logic [2].
In function, Mahuang Decoction is pungent-warm, induces sweating, and diffuses the lung to relieve wheezing [3][4]. Guizhi Decoction is pungent-warm, releases the muscle layer and harmonizes the nutritive and defensive qi [5][6][7][8][9]. …
In indications they differ markedly: both release the exterior with pungent-warm herbs, but Mahuang Decoction has a stronger diaphoretic effect and suits exterior-excess patterns without sweating …
引用溯源 / Citation tracing:点击角标 [3],右侧面板显示「精确命中」的原文出处与段落: Clicking marker [3] opens the side panel showing an exact match to its source passage:
出处 / Source:伤寒论临床运用 › 第二章 太阳病辨证论治 › 第二节 太阳病本证证治 › 二、太阳伤寒表实证 › (一)麻黄汤证 › 【方药精解】 › 宣肺平喘
引用句 / Cited sentence:在功效方面,麻黄汤具有辛温发汗、宣肺平喘的功效
原文 / Passage:宣肺平喘:麻黄又有宣肺平喘之功,杏仁,宣肺降气,助麻黄平喘。……

输入 / Input
治疗风寒表实证的代表方是:A. 桂枝汤 B. 麻黄汤 C. 银翘散 D. 小青龙汤 E. 九味羌活汤。请给出答案并说明理由。
Which is the representative formula for the wind-cold exterior-excess pattern? A. Guizhi Decoction B. Mahuang Decoction C. Yinqiao Powder D. Xiao Qinglong Decoction E. Jiuwei Qianghuo Decoction. Give the answer and explain why.
输出 / Output
{
"answer": "B",
"rationale": "风寒表实证(又称风寒束肺证或太阳伤寒证)的病机为风寒外束肌表,导致卫阳被遏、营阴郁滞、肺气失宣[1][2][3]。其治疗原则是疏风散寒、宣肺止咳[4]。麻黄汤出自《伤寒论》,是治疗风寒表实证的代表方剂[5],具有发汗解表、宣肺平喘的功效[6][7][8]。方中麻黄为君药,发汗散寒、宣肺平喘[9];桂枝为臣药,助麻黄发汗解肌[10];杏仁为佐药,降利肺气以助平喘[11]。因此,治疗风寒表实证的代表方是麻黄汤[12]。桂枝汤主要用于风寒表虚证[13],银翘散用于风热表证,小青龙汤用于外寒内饮证[14],均非风寒表实证的首选代表方。"
}
{
"answer": "B",
"rationale": "The wind-cold exterior-excess pattern (also called Taiyang cold damage) arises when wind-cold fetters the exterior, constraining defensive yang, stagnating nutritive yin and impairing the lung's diffusing function [1][2][3]. Treatment is to disperse wind-cold and diffuse the lung [4]. Mahuang Decoction, from the Shanghan Lun, is the representative formula for this pattern [5]; it induces sweating to release the exterior and diffuses the lung to relieve wheezing [6][7][8]. Mahuang is the sovereign herb, inducing sweating and dispersing cold [9]; Guizhi is the minister, assisting sweating and releasing the muscle layer [10]; Xingren is the assistant, directing lung qi downward to aid in relieving wheezing [11]. Hence the answer is Mahuang Decoction [12]. Guizhi Decoction treats the exterior-deficiency pattern [13], Yinqiao Powder treats wind-heat exterior patterns, and Xiao Qinglong Decoction treats external cold with internal fluid retention [14]; none is the first-choice formula here."
}
免责声明 / Disclaimer:本模型仅用于研究与教学,输出内容不构成医疗建议,不能替代执业医师的诊断与治疗。 This model is intended for research and educational purposes only. Its outputs do not constitute medical advice and must not replace diagnosis or treatment by a licensed physician.
使用 uv 安装依赖:
uv pip install -U torch transformers accelerate huggingface_hub
如果仓库为私有,请先使用有访问权限的账号登录:
uv tool run --from huggingface_hub hf auth login
在模型权重上传完成后运行以下示例。示例需要足够内存或显存,具体需求取决于设备和输入长度。
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "GancaoDoctorAI/TraceMed"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
dtype="auto",
device_map="auto",
)
model.eval()
messages = [{"role": "user", "content": "你好,请介绍一下你自己。"}]
prompt = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
)
inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256, do_sample=False)
reply = outputs[0, inputs["input_ids"].shape[1]:]
print(tokenizer.decode(reply, skip_special_tokens=True))
model.safetensors:模型权重。config.json:模型结构配置。generation_config.json:默认生成配置。tokenizer.json、tokenizer_config.json:分词器及配置。chat_template.jinja:对话输入模板。基础模型来源、训练数据、评测结果与许可证信息待补充。