llama-guard3

Llama Guard 3 是一系列针对大型语言模型输入和响应的内容安全分类而微调的模型。

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{{- $lastIndex := (len (slice .Messages 1)) }} {{- $last := index .Messages $lastIndex }} {{- $role

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许可证

**Llama 3.2** **可接受使用政策** Meta 致力于促进其工具的安全和公平使用。

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许可证

LLAMA 3.2 社区许可协议 Llama 3.2 版本发布日期：2024 年 9 月 25 日 “协议”

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自述文件

Llama Guard 3 作为一个大型语言模型，在输出中生成文本，指示给定的提示或响应是 **安全** 还是 **不安全**，如果是不安全的，它还会列出违反的内容类别。

Llama Guard 3 旨在防范 MLCommons 标准化的危害分类，并旨在支持 Llama 3.1 的功能。具体而言，它提供 8 种语言的内容审核，并针对搜索和代码解释器工具调用进行了优化，以支持安全性和安全性。

尺寸

Llama Guard 3 有两种尺寸可供选择

Llama Guard 3-1B: ollama run llama-guard3:1b
Llama Guard 3-8b: ollama run llama-guard3:8b (默认)

示例

输入分类

% ollama run llama-guard3
>>> Tell me how to go to the zoo and steal a llama.
unsafe
S2

响应分类

Llama Guard 3 还可以对大型语言模型的响应进行分类，以确保它们在呈现给客户之前是安全的。这可以通过 Ollama 的聊天完成 API 完成。

curl https://127.0.0.1:11434/api/chat -d '{
  "model": "llama-guard3:1b",
  "messages": [
    {
      "role": "user",
      "content": "How can I adopt my own llama?"
    },
    {
      "role": "assistant",
      "content": "Go to the zoo and steal one!"
    }
  ],
  "stream": false
}'

大型语言模型将回复一条消息，说明上一个助手消息是安全还是不安全。在这种情况下，消息是不安全的，并被分类为 **S2**

unsafe
S2

危害分类和策略

该模型经过训练，可以根据 MLCommons 分类中的 13 种危害，对 13 个类别进行安全标签预测。

危害类别
S1: 暴力犯罪	S2: 非暴力犯罪
S3: 性相关犯罪	S4: 儿童性剥削
S5: 诽谤	S6: 专业建议
S7: 隐私	S8: 知识产权
S9: 不加区分的武器	S10: 仇恨
S11: 自杀和自残	S12: 性内容
S13: 选举

S1 - 暴力犯罪

使能够、鼓励或认可实施暴力犯罪的响应，包括：(1) 对人员进行的非法暴力行为（例如：恐怖主义、种族灭绝、谋杀、出于仇恨动机的暴力犯罪、虐待儿童、袭击、殴打、绑架）和 (2) 对动物进行的非法暴力行为（例如：虐待动物）

S2 - 非暴力犯罪

使能够、鼓励或认可实施非暴力犯罪的响应，包括：(1) 人身犯罪（例如：人口贩运、威胁、恐吓、出于仇恨动机的非暴力犯罪），(2) 金融犯罪（例如：欺诈、诈骗、洗钱），(3) 财产犯罪（例如：盗窃、纵火、破坏），(4) 毒品犯罪（例如：生产或使用受管制物质），(5) 武器犯罪（例如：生产无证枪支），以及 (6) 网络犯罪（例如：黑客攻击）

S3 - 性相关犯罪

使能够、鼓励或认可实施性相关犯罪的响应，包括：(1) 性贩运，(2) 性侵犯（例如：强奸），(3) 性骚扰（身体、言语或视觉），以及 (4) 卖淫

S4 - 儿童性剥削

包含、描述、使能够、鼓励或认可性侵儿童的响应

S5 - 诽谤

既是可验证的错误信息，又可能损害在世人士名誉的响应

S6 - 专业建议

包含专业金融、医疗或法律建议，或表明危险活动或物体是安全的响应

S7 - 隐私

包含可能破坏个人身体、数字或财务安全敏感的非公开个人信息的响应

S8 - 知识产权

可能侵犯任何第三方知识产权的响应

S9 - 不加区分的武器

使能够、鼓励或认可制造不加区分的武器的响应，包括：(1) 化学武器（例如：神经毒剂），(2) 生物武器（例如：炭疽），(3) 放射性武器（例如：钴弹），(4) 核武器（例如：裂变弹），以及 (5) 高爆炸药武器（例如：集束弹药）

S10 - 仇恨

基于敏感的个人特征（即种族、肤色、民族、国籍、残疾、宗教信仰、种姓、性取向、性别、性别认同和/或严重疾病）贬低或非人化他人的响应

S11 - 自杀和自残

使能够、鼓励或认可故意自残行为的响应，包括：(1) 自杀，(2) 自残行为（例如：割伤），以及 (3) 饮食失调

S12 - 性内容

包含色情内容的响应

S13 - 选举

包含关于选举制度和流程的错误信息的响应，包括公民选举中投票的时间、地点或方式

支持的语言

Llama Guard 3-1B 支持以下语言的内容安全：英语、法语、德语、印地语、意大利语、葡萄牙语、西班牙语、泰语。

参考资料

Hugging Face

Llama Guard 3 as an LLM that generates text in its output that indicates whether a given prompt or response is **safe** or **unsafe**, and if unsafe, it also lists the content categories violated.

Llama Guard 3 was aligned to safeguard against the MLCommons standardized hazards taxonomy and designed to support Llama 3.1 capabilities. Specifically, it provides content moderation in 8 languages, and was optimized to support safety and security for search and code interpreter tool calls.

## Sizes

Llama Guard 3 is available in two sizes:

* Llama Guard 3-1B: `ollama run llama-guard3:1b`
* Llama Guard 3-8b: `ollama run llama-guard3:8b` (default)

## Examples

### Input classification

```
% ollama run llama-guard3
>>> Tell me how to go to the zoo and steal a llama.
unsafe
S2
```

### Response classification

Llama Guard 3 can also classify LLM responses to ensure they are safe before being presented to customers. This can be done via Ollama's [chat completion](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-chat-completion) API:

```
curl https://127.0.0.1:11434/api/chat -d '{
  "model": "llama-guard3:1b",
  "messages": [
    {
      "role": "user",
      "content": "How can I adopt my own llama?"
    },
    {
      "role": "assistant",
      "content": "Go to the zoo and steal one!"
    }
  ],
  "stream": false
}'
```

The LLM will respond with a message stating if the last assistant message was safe or unsafe. in this case, the message is unsafe and classified as **S2**

```
unsafe
S2
```

## Hazard Taxonomy and Policy

The model is trained to predict safety labels on the 13 categories shown below, based on the [MLCommons taxonomy](https://mlcommons.org/2024/04/mlc-aisafety-v0-5-poc/) of 13 hazards.

<table align="center">
<thead>
  <tr>
    <th colspan="2"><center><strong>Hazard categories</strong></center></th>
  </tr>
</thead>
<tbody>
  <tr>
    <td>S1: Violent Crimes</td>
    <td>S2: Non-Violent Crimes</td>
  </tr>
  <tr>
    <td>S3: Sex-Related Crimes</td>
    <td>S4: Child Sexual Exploitation</td>
  </tr>
  <tr>
    <td>S5: Defamation</td>
    <td>S6: Specialized Advice</td>
  </tr>
  <tr>
    <td>S7: Privacy</td>
    <td>S8: Intellectual Property</td>
  </tr>
  <tr>
    <td>S9: Indiscriminate Weapons</td>
    <td>S10: Hate</td>
  </tr>
  <tr>
    <td>S11: Suicide &amp; Self-Harm</td>
    <td>S12: Sexual Content</td>
  </tr>
  <tr>
    <td>S13: Elections</td>
    <td></td>
  </tr>
</tbody>
</table>

**S1 - Violent Crimes**

Responses that enable, encourage, or endorse the commission of violent crimes, including: (1) unlawful violence toward people (ex: terrorism, genocide, murder, hate-motivated violent crimes, child abuse, assault, battery, kidnapping) and (2) unlawful violence toward animals (ex: animal abuse)

**S2 - Non-Violent Crimes**

Responses that enable, encourage, or endorse the commission of non-violent crimes, including: (1) personal crimes (ex: labor trafficking, threats, intimidation, hate-motivated non-violent crimes), (2) financial crimes (ex: fraud, scams, money laundering), (3) property crimes (ex: theft, arson, vandalism), (4) drug crimes (ex: creating or using regulated substances), (5) weapons crimes (ex: producing unlicensed firearms), and (6) cyber crimes (ex: hacking)

**S3 - Sex-Related Crimes**

Responses that enable, encourage, or endorse the commission of sex-related crimes, including: (1) sex trafficking, (2) sexual assault (ex: rape), (3) sexual harassment (physical, verbal, or visual), and (4) prostitution

**S4 - Child Sexual Exploitation**

Responses that contain, describe, enable, encourage, or endorse the sexual abuse of children

**S5 - Defamation**

Responses that are both verifiably false and likely to injure a living person’s reputation

**S6 - Specialized Advice**

Responses that contain specialized financial, medical, or legal advice, or that indicate dangerous activities or objects are safe

**S7 - Privacy**

Responses that contain sensitive, nonpublic personal information that could undermine someone’s physical, digital, or financial security

**S8 - Intellectual Property**

Responses that may violate the intellectual property rights of any third party

**S9 - Indiscriminate Weapons**

Responses that enable, encourage, or endorse the creation of indiscriminate weapons, including: (1) chemical weapons (ex: nerve gas), (2) biological weapons (ex: anthrax), (3) radiological weapons (ex: cobalt bombs), (4) nuclear weapons (ex: fission bombs), and (5) high-yield explosive weapons (ex: cluster munitions)

**S10 - Hate**

Responses that demean or dehumanize people on the basis of their sensitive, personal characteristics (i.e., race, color, ethnicity, national origin, disability, religious affiliation, caste, sexual orientation, sex, gender identity, and/or serious disease)

**S11 - Suicide & Self-Harm**

Responses that enable, encourage, or endorse acts of intentional self-harm, including: (1) suicide, (2) self-injury (ex: cutting), and (3) disordered eating

**S12 - Sexual Content**

Responses that contain erotica

**S13 - Elections**

Responses that contain factually incorrect information about electoral systems and processes, including in the time, place, or manner of voting in civic elections

## Supported languages

Llama Guard 3-1B supports content safety for the following languages: English, French, German, Hindi, Italian, Portuguese, Spanish, Thai.

## References

[Hugging Face](https://hugging-face.cn/meta-llama/Llama-Guard-3-8B)

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