Using Llama Guard 7B on Together AI
Implementation guide · Llama Guard · AI at Meta
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
llama-guard-7b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYllama-guard-7bTogether uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="llama-guard-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)About Together AI
Platform for running open-source and proprietary LLMs
Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Pricing on Together 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. This makes it an invaluable tool for AI engineers focused on deploying safe and responsible AI systems. For more information, visit the model's page on Hugging Face .