Using Llama Guard 7B on Fireworks AI
Implementation guide · Llama Guard · AI at Meta
Fireworks AI exposes Llama Guard 7B through model ID accounts/fireworks/models/llamaguard-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-09. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/llamaguard-7b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/llamaguard-7bFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llamaguard-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About Llama Guard 7B
Llama Guard 7B is a specialized content moderation model based on the Llama 2 architecture, designed to safeguard AI interactions. With 7 billion parameters, it excels in classifying and moderating both input prompts and output responses from large language models. The model employs a comprehensive risk taxonomy to identify various categories of harmful content, including violence, hate speech, and sexual content. Trained on diverse datasets, including prompts from the Anthropic dataset and in-house generated responses, Llama Guard 7B has demonstrated superior performance compared to industry-standard content moderation APIs.