Instructions to use antoniostepien/peer-ai-reviewer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use antoniostepien/peer-ai-reviewer with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="antoniostepien/peer-ai-reviewer",
	filename="peer-ai-q4km.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use antoniostepien/peer-ai-reviewer with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf antoniostepien/peer-ai-reviewer
# Run inference directly in the terminal:
llama-cli -hf antoniostepien/peer-ai-reviewer

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf antoniostepien/peer-ai-reviewer
# Run inference directly in the terminal:
llama-cli -hf antoniostepien/peer-ai-reviewer

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf antoniostepien/peer-ai-reviewer
# Run inference directly in the terminal:
./llama-cli -hf antoniostepien/peer-ai-reviewer

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf antoniostepien/peer-ai-reviewer
# Run inference directly in the terminal:
./build/bin/llama-cli -hf antoniostepien/peer-ai-reviewer

Use Docker

docker model run hf.co/antoniostepien/peer-ai-reviewer

LM Studio
Jan

vLLM

How to use antoniostepien/peer-ai-reviewer with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "antoniostepien/peer-ai-reviewer"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "antoniostepien/peer-ai-reviewer",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/antoniostepien/peer-ai-reviewer

Ollama
How to use antoniostepien/peer-ai-reviewer with Ollama:
```
ollama run hf.co/antoniostepien/peer-ai-reviewer
```

Unsloth Studio new

How to use antoniostepien/peer-ai-reviewer with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for antoniostepien/peer-ai-reviewer to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for antoniostepien/peer-ai-reviewer to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for antoniostepien/peer-ai-reviewer to start chatting

Pi new

How to use antoniostepien/peer-ai-reviewer with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf antoniostepien/peer-ai-reviewer

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "antoniostepien/peer-ai-reviewer"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use antoniostepien/peer-ai-reviewer with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf antoniostepien/peer-ai-reviewer

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default antoniostepien/peer-ai-reviewer

Run Hermes

hermes

Docker Model Runner
How to use antoniostepien/peer-ai-reviewer with Docker Model Runner:
```
docker model run hf.co/antoniostepien/peer-ai-reviewer
```

Lemonade

How to use antoniostepien/peer-ai-reviewer with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull antoniostepien/peer-ai-reviewer

Run and chat with the model

lemonade run user.peer-ai-reviewer-{{QUANT_TAG}}

List all available models

lemonade list

Peer-AI Code Reviewer

AI-powered code security reviewer fine-tuned on security vulnerability patterns.

Model Description

Peer-AI is a Qwen2.5-Coder-1.5B model fine-tuned with LoRA for code security review tasks. It can identify common security vulnerabilities including:

CWE-78: Command Injection
CWE-89: SQL Injection
CWE-22: Path Traversal
CWE-79: Cross-Site Scripting (XSS)
CWE-94: Code Injection
CWE-120: Buffer Overflow
CWE-190: Integer Overflow
CWE-416: Use After Free
CWE-502: Deserialization
CWE-798: Hardcoded Credentials

Languages Supported

Python
Go
C/C++
Rust
JavaScript/TypeScript

Usage

With Ollama

# Create model
ollama create peer-ai -f Modelfile

# Review code
curl -s http://localhost:11434/api/generate -d '{
  "model": "peer-ai",
  "prompt": "Review the following python code...",
  "stream": false
}'

With CLI

pip install peer-ai
git diff | peer-ai review -
peer-ai review src/main.py

Training

Base Model: Qwen/Qwen2.5-Coder-1.5B-Instruct
Method: QLoRA (r=16, alpha=32)
Dataset: 223 security vulnerability examples
Epochs: 3
Final Loss: 0.21

Output Format

{
  "line": 2,
  "severity": "high",
  "category": "security",
  "rule": "CWE-78",
  "title": "Command injection vulnerability",
  "message": "User input passed to shell command.",
  "suggestion": "Use subprocess with shell=False."
}

License

Apache 2.0

Model tree for antoniostepien/peer-ai-reviewer

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-Coder-1.5B

Finetuned

Qwen/Qwen2.5-Coder-1.5B-Instruct

Quantized

(92)

this model

antoniostepien
/

peer-ai-reviewer