llama-guard3:1b-q8_0

llama-guard3

Llama Guard 3 是一系列针对大型语言模型 (LLM) 输入和输出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

1.2kB

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

7.7kB

自述文件

Llama Guard 3 作为一个大型语言模型，在其输出文本中生成指示给定提示或回复是否**安全**或**不安全**的信息，如果是不安全，还会列出违反的内容类别。

Llama Guard 3 符合 MLCommons 标准化危害分类法的保护标准，并设计为支持 Llama 3.1 的功能。具体来说，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安全性和可靠性优化。

尺寸

Llama Guard 3 提供两种尺寸

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

输出分类

Llama Guard 3 还可以对大型语言模型的回复进行分类，以确保其安全后再呈现给客户。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
}'

LLM 将回复一条消息，说明上一条助手消息是安全还是不安全。在本例中，该消息不安全，并被分类为**S2**。

unsafe
S2

危害分类法和政策

该模型经过训练，可以根据以下显示的 13 个类别预测安全标签，这些类别基于MLCommons 分类法的 13 种危害。

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：杀伤性武器	S10：仇恨
S11：自杀和自残	S12：色情内容
S13：选举

S1 - 暴力犯罪

可能促成、鼓励或认可暴力犯罪的回复，包括：(1) 对人的非法暴力（例如：恐怖主义、种族灭绝、谋杀、仇恨动机暴力犯罪、虐待儿童、袭击、殴打、绑架）和 (2) 对动物的非法暴力（例如：虐待动物）。

S2 - 非暴力犯罪

可能促成、鼓励或认可非暴力犯罪的回复，包括：(1) 人身犯罪（例如：劳工贩卖、威胁、恐吓、仇恨动机非暴力犯罪），(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：制造或使用受管制物质），(5) 武器犯罪（例如：制造未经许可的枪支）和 (6) 网络犯罪（例如：黑客攻击）。

S3 - 性相关犯罪

可能促成、鼓励或认可性相关犯罪的回复，包括：(1) 性贩卖，(2) 性侵犯（例如：强奸），(3) 性骚扰（身体、言语或视觉），和 (4) 卖淫。

S4 - 儿童性剥削

包含、描述、促成、鼓励或认可对儿童性虐待的回复。

S5 - 诽谤

既可验证为虚假且可能损害在世者声誉的回复。

S6 - 专业建议

包含专业的财务、医疗或法律建议，或表明危险活动或物品安全的回复。

S7 - 隐私

包含可能破坏他人身心或财务安全的敏感的非公开个人信息的回复。

S8 - 知识产权

可能侵犯任何第三方知识产权的回复。

S9 - 杀伤性武器

可能促成、鼓励或认可制造杀伤性武器的回复，包括：(1) 化学武器（例如：神经毒气），(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）和 (5) 高当量爆炸性武器（例如：集束弹药）。

S10 - 仇恨

基于其敏感的个人特征（即种族、肤色、民族、原籍国、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回复。

S11 - 自杀和自残

可能促成、鼓励或认可蓄意自残行为的回复，包括：(1) 自杀，(2) 自残（例如：割伤）和 (3) 饮食失调。

S12 - 色情内容

包含色情内容的回复。

S13 - 选举

包含关于选举制度和流程的虚假信息的回复，包括公民选举的投票时间、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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