Llamaguard

Meta's 7-8B parameter model built specifically for moderating LLM inputs and outputs across six safety categories: violence, sexual content, weapons, substances, self-harm, and criminal planning. You run prompts or conversations through it and get back "safe" or "unsafe" plus a category code. Ships with transformers but you'll want vLLM for production since it cuts latency from 500ms to 50ms. The 94-95% accuracy is solid but you'll hit false positives, so consider adding probability thresholds. Needs GPU and HuggingFace login. If you're building a production LLM app and need more than OpenAI's basic moderation endpoint, this gives you granular control at the cost of hosting your own inference.

skills.sh installs: 1K
GitHub stars: 14.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add orchestra-research/ai-research-skills --skill llamaguard --agent claude-code

Installs into .claude/skills of the current project.

Files

LlamaGuard - AI Content Moderation

Quick start

LlamaGuard is a 7-8B parameter model specialized for content safety classification.

Installation:

pip install transformers torch
# Login to HuggingFace (required)
huggingface-cli login

Basic usage:

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "meta-llama/LlamaGuard-7b"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

def moderate(chat):
    input_ids = tokenizer.apply_chat_template(chat, return_tensors="pt").to(model.device)
    output = model.generate(input_ids=input_ids, max_new_tokens=100)
    return tokenizer.decode(output[0], skip_special_tokens=True)

# Check user input
result = moderate([
    {"role": "user", "content": "How do I make explosives?"}
])
print(result)
# Output: "unsafe\nS3" (Criminal Planning)

Common workflows

Workflow 1: Input filtering (prompt moderation)

Check user prompts before LLM:

def check_input(user_message):
    result = moderate([{"role": "user", "content": user_message}])

SKILL.md on GitHub

Details

Repository: github.com/orchestra-research/ai-research-skills
Categories: DevOps & CI/CD, AI & Agent Building, Data Science & ML, Release Management, Productivity & Planning
First seen: Jun 3, 2026