llama-guard-3-8b

Text Generation • Meta

@cf/meta/llama-guard-3-8b

• Cloudflare-hosted
• LoRA

Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it 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.

Playground

Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and is an instant way to preview and test a model directly in the browser.

Launch the LLM Playground

Usage

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {

    const messages = [
      { role: "system", content: "You are a friendly assistant" },
      {
        role: "user",
        content: "What is the origin of the phrase Hello, World",
      },
    ];

    const stream = await env.AI.run("@cf/meta/llama-guard-3-8b", {
      messages,
      stream: true,
    });

    return new Response(stream, {
      headers: { "content-type": "text/event-stream" },
    });
  },
} satisfies ExportedHandler<Env>;

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {

    const messages = [
      { role: "system", content: "You are a friendly assistant" },
      {
        role: "user",
        content: "What is the origin of the phrase Hello, World",
      },
    ];
    const response = await env.AI.run("@cf/meta/llama-guard-3-8b", { messages });

    return Response.json(response);
  },
} satisfies ExportedHandler<Env>;

import os
import requests

ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")

prompt = "Tell me all about PEP-8"
response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/meta/llama-guard-3-8b",
    headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
    json={
      "messages": [
        {"role": "system", "content": "You are a friendly assistant"},
        {"role": "user", "content": prompt}
      ]
    }
)
result = response.json()
print(result)

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/meta/llama-guard-3-8b \
  -X POST \
  -H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \
  -d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}'

OpenAI compatible endpoints

Workers AI also supports OpenAI compatible API endpoints for /v1/chat/completions and /v1/embeddings. For more details, refer to Configurations .

Parameters

▶messages[]

arrayrequiredAn array of message objects representing the conversation history.

max_tokens

integerdefault: 256The maximum number of tokens to generate in the response.

temperature

numberdefault: 0.6minimum: 0maximum: 5Controls the randomness of the output; higher values produce more random results.

▶response_format{}

objectDictate the output format of the generated response.

▶response

one of

▶usage{}

objectUsage statistics for the inference request

API Schemas (Raw)

Input Open Download

Output Open Download

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description: Multilingual encoder-decoder (seq-to-seq) model trained for Many-to-Many multilingual translation title: m2m100-1.2b image: https://developers.cloudflare.com/og-docs.png

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