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LICENSE

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+META LLAMA 3 COMMUNITY LICENSE AGREEMENT
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README.md

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+## WiNGPT2
+
+[WiNGPT](https://github.com/winninghealth/WiNGPT2) 是一个基于GPT的医疗垂直领域大模型，旨在将专业的医学知识、医疗信息、数据融会贯通，为医疗行业提供智能化的医疗问答、诊断支持和医学知识等信息服务，提高诊疗效率和医疗服务质量。
+
+## 更新日志
+
+[2024/04/23] 更新 WiNGPT2-Llama-3-8B-Base 和 WiNGPT2-Llama-3-8B-Chat 模型（中文增强/多语言）与测评结果
+
+[2024/04/01] 更新 WiNEval 测评结果
+
+[2024/03/05] 开源7B/14B-Chat-4bit模型权重: [🤗](https://huggingface.co/winninghealth/WiNGPT2-7B-Chat-AWQ)WiNGPT2-7B-Chat-4bit和[🤗](https://huggingface.co/winninghealth/WiNGPT2-14B-Chat-AWQ)WiNGPT2-14B-Chat-4bit。
+
+[2023/12/20] 新增用户微信群二维码，有效期到12月27日，扫码进群。
+
+[2023/12/18] 发布卫宁健康医疗模型测评方案 WiNEval-MCKQuiz的评测结果。
+
+[2023/12/12] 开源 WiNGPT2 14B模型权重: [🤗](https://huggingface.co/winninghealth/WiNGPT2-14B-Base)WiNGPT2-14B-Base 和 [🤗](https://huggingface.co/winninghealth/WiNGPT2-14B-Chat)WiNGPT2-14B-Chat。 
+
+[2023/11/02] [34B模型平台测试](https://wingpt.winning.com.cn/) 和 [欢迎加入微信讨论群](https://github.com/winninghealth/WiNGPT2/blob/main/assets/WiNGPT_GROUP.JPG)
+
+[2023/10/13] 更新一个简单的[Chatbot示例](#部署)，可以进行简单的多轮对话。
+
+[2023/09/26] 开源 WiNGPT2 与7B模型权重: [🤗](https://huggingface.co/winninghealth/WiNGPT2-7B-Base)WiNGPT2-7B-Base 和 [🤗](https://huggingface.co/winninghealth/WiNGPT2-7B-Chat)WiNGPT2-7B-Chat。 
+
+## 如何使用
+
+### 推理
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "WiNGPT-Llama-3-8B-Chat"
+device = "cuda"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path).to(device)
+model = model.eval()
+
+
+text = 'User：WiNGPT, 你好<|end_of_text|>\n Assistant：'
+inputs = tokenizer.encode(text, return_tensors="pt").to(device)
+outputs = model.generate(inputs, repetition_penalty=1.1, max_new_tokens=1024)
+response = tokenizer.decode(outputs[0])
+print(response)
+
+## 输出结果：你好！今天我能为你做些什么？<|end_of_text|>
+```
+
+### 提示
+
+WiNGPT-Llama-3-8B-Chat 使用了自定义的提示格式：
+
+用户角色：System/User/Assistant
+
+chat_template:
+
+```jinja2
+"{% for message in messages %}{% if message['role'] == 'system' %}System：{% endif %}{% if message['role'] == 'user' %}User：{% endif %}{% if message['role'] == 'assistant' %}Assistant：{% endif %}{{ message['content'] }}<|end_of_text|>\n {% endfor %}Assistant："
+```
+
+**指令提示**示例：
+
+```
+User：WiNGPT, 你好<|end_of_text|>\n Assistant：
+```
+
+**多轮对话**示例：
+
+```
+User：WiNGPT, 你好<|end_of_text|>\n Assistant：你好！今天我能为你做些什么？<|end_of_text|>\n User：你是谁？<|end_of_text|>\n Assistant：
+```
+
+**翻译功能**示例：
+
+```
+System：作为医疗领域的智能助手，WiNGPT将提供中英翻译服务。用户输入的中文或英文内容将由WiNGPT进行准确的翻译，以满足用户的语言需求。<|end_of_text|>\n User：Life is short, you know, and time is so swift; Rivers are wide, so wide, and ships sail far.<|end_of_text|>\n Assistant：
+```
+
+## 模型卡
+
+####  训练配置与参数
+
+| 名称                    | 训练策略           | 长度 | 精度 | 学习率 | Weight_decay | Epochs | GPUs   |
+| ----------------------- | ------------------ | ---- | ---- | ------ | ------------ | ------ | ------ |
+| WiNGPT2-Llama-3-8B-Base | 继续预训练 (20G)   | 8192 | bf16 | 5e-5   | 0.05         | 2      | A100*8 |
+| WiNGPT2-Llama-3-8B-Chat | 微调/对齐 (50万条) | 8192 | bf16 | 5e-6   | 0.01         | 4      | A100*8 |
+
+#### 训练数据
+
+预训练数据约20G，指令微调对齐数据约50万条，[详细内容](https://github.com/winninghealth/WiNGPT2?tab=readme-ov-file#%E8%AE%AD%E7%BB%83%E6%95%B0%E6%8D%AE) 。
+
+## 中文医疗评测 - WiNEval
+
+更新时间：2024-04-23
+|                               | Type                   | MCKQuiz | MSceQA |
+| ----------------------------- | ---------------------- | ------- | ------ |
+| **WiNGPT-Llama-3-8B-Base**    | Continued Pre-training | 66.3    | /      |
+| Meta-Llama-3-8B               | Pre-training           | 37      | /      |
+|                               |                        |         |        |
+| **WiNGPT-Llama-3-8B-Chat**    | Finetuning/Alignment   | 65.2    | 83.5   |
+| Meta-Llama-3-8B-Instruct      | Finetuning/Alignment   | 49.8    | 76.3   |
+| Meta-Llama-3-70B-Instruct-AWQ | Finetuning/Alignment   | 73.5    | 78.6   |
+|                               |                        |         |        |
+
+*MCKQuiz（客观题）：17个科目分类13060选择题；输入问题和选项，让模型输出答案。根据标准答案判断对错，统计准确率。*
+
+*MSceQA（主观题）：由细分领域场景题目构成，包含八��业务场景，17个一级分类和32个二级分类。使用人工/模型对模型的回答进行准确性、相关性、一致性、完整性、权威性评价，并参照标准答案对模型生成的答案进行评分。*
+
+[其他WiNEval评测结果](https://github.com/winninghealth/WiNGPT2?tab=readme-ov-file#2-%E5%8D%AB%E5%AE%81%E5%81%A5%E5%BA%B7%E5%8C%BB%E7%96%97%E6%A8%A1%E5%9E%8B%E6%B5%8B%E8%AF%84%E6%96%B9%E6%A1%88-winevalzero-shot)
+
+### 企业服务
+
+[通过WiNGPT测试平台申请密钥或与我们取得联系](https://wingpt.winning.com.cn/)
+
+
+## 局限性与免责声明
+
+(a) WiNGPT2 是一个专业医疗领域的大语言模型，可为一般用户提供拟人化AI医生问诊和问答功能，以及一般医学领域的知识问答。对于专业医疗人士，WiNGPT2 提供关于患者病情的诊断、用药和健康建议等方面的回答的建议仅供参考。
+
+(b) 您应理解 WiNGPT2 仅提供信息和建议，不能替代医疗专业人士的意见、诊断或治疗建议。在使用 WiNGPT2 的信息之前，请寻求医生或其他医疗专业人员的建议，并独立评估所提供的信息。
+
+(c) WiNGPT2 的信息可能存在错误或不准确。卫宁健康不对 WiNGPT2 的准确性、可靠性、完整性、质量、安全性、及时性、性能或适用性提供任何明示或暗示的保证。使用 WiNGPT2 所产生的结果和决策由您自行承担。第三方原因而给您造成的损害结果承担责任。
+
+## 许可证
+
+1. 本项目授权协议为 Apache License 2.0，模型权重需要遵守基础模型 [Llama-3-8B](https://github.com/meta-llama/llama3) 相关协议及其[许可证](https://llama.meta.com/llama3/license)，详细内容参照其网站。
+
+2. 使用本项目包括模型权重时请引用本项目：https://github.com/winninghealth/WiNGPT2
+
+## 联系我们
+
+网站：https://www.winning.com.cn
+
+邮箱：wair@winning.com.cn

USE_POLICY.md

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+# Meta Llama 3 Acceptable Use Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Meta Llama 3. If you
+access or use Meta Llama 3, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
+this policy can be found at [https://llama.meta.com/llama3/use-policy](https://llama.meta.com/llama3/use-policy)
+
+## Prohibited Uses
+
+We want everyone to use Meta Llama 3 safely and responsibly. You agree you will not use, or allow
+others to use, Meta Llama 3 to:
+
+1. Violate the law or others’ rights, including to:
+    1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
+        1. Violence or terrorism
+        2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
+        3. Human trafficking, exploitation, and sexual violence
+        4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
+        5. Sexual solicitation
+        6. Any other criminal activity
+    2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
+    3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
+    4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
+    5. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
+    6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials
+    7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
+
+2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Meta Llama 3 related to the following:
+    1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
+    2. Guns and illegal weapons (including weapon development)
+    3. Illegal drugs and regulated/controlled substances
+    4. Operation of critical infrastructure, transportation technologies, or heavy machinery
+    5. Self-harm or harm to others, including suicide, cutting, and eating disorders
+    6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
+
+3. Intentionally deceive or mislead others, including use of Meta Llama 3 related to the following:
+    1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+    2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+    3. Generating, promoting, or further distributing spam
+    4. Impersonating another individual without consent, authorization, or legal right
+    5. Representing that the use of Meta Llama 3 or outputs are human-generated
+    6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
+
+4. Fail to appropriately disclose to end users any known dangers of your AI system
+
+Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation
+of this Policy through one of the following means:
+
+● Reporting issues with the model: [https://github.com/meta-llama/llama3](https://github.com/meta-llama/llama3)
+● Reporting risky content generated by the model:
+developers.facebook.com/llama_output_feedback
+● Reporting bugs and security concerns: facebook.com/whitehat/info
+● Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3:
+LlamaUseReport@meta.com

config.json

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+{
+  "_name_or_path": "WiNGPT2-Llama-3-8B-Chat",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.0",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "transformers_version": "4.40.0"
+}

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special_tokens_map.json

@@ -0,0 +1,17 @@
+{
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+    "single_word": false
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+  "pad_token": "<|end_of_text|>"
+}

tokenizer_config.json

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