Instructions to use nu11secur1ty/nu11secur1tyAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use nu11secur1ty/nu11secur1tyAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="nu11secur1ty/nu11secur1tyAI", filename="nu11secur1tyAI4-Evolution-Laptop-Q4_KM.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use nu11secur1ty/nu11secur1tyAI with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf nu11secur1ty/nu11secur1tyAI # Run inference directly in the terminal: llama-cli -hf nu11secur1ty/nu11secur1tyAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf nu11secur1ty/nu11secur1tyAI # Run inference directly in the terminal: llama-cli -hf nu11secur1ty/nu11secur1tyAI
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 nu11secur1ty/nu11secur1tyAI # Run inference directly in the terminal: ./llama-cli -hf nu11secur1ty/nu11secur1tyAI
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 nu11secur1ty/nu11secur1tyAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf nu11secur1ty/nu11secur1tyAI
Use Docker
docker model run hf.co/nu11secur1ty/nu11secur1tyAI
- LM Studio
- Jan
- vLLM
How to use nu11secur1ty/nu11secur1tyAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nu11secur1ty/nu11secur1tyAI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nu11secur1ty/nu11secur1tyAI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nu11secur1ty/nu11secur1tyAI
- Ollama
How to use nu11secur1ty/nu11secur1tyAI with Ollama:
ollama run hf.co/nu11secur1ty/nu11secur1tyAI
- Unsloth Studio
How to use nu11secur1ty/nu11secur1tyAI 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 nu11secur1ty/nu11secur1tyAI 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 nu11secur1ty/nu11secur1tyAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nu11secur1ty/nu11secur1tyAI to start chatting
- Docker Model Runner
How to use nu11secur1ty/nu11secur1tyAI with Docker Model Runner:
docker model run hf.co/nu11secur1ty/nu11secur1tyAI
- Lemonade
How to use nu11secur1ty/nu11secur1tyAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull nu11secur1ty/nu11secur1tyAI
Run and chat with the model
lemonade run user.nu11secur1tyAI-{{QUANT_TAG}}List all available models
lemonade list
Update README.md
Browse files
README.md
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--repeat-penalty 1.1 \
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--color \
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-i -r "User:"
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--repeat-penalty 1.1 \
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-i -r "User:"
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```
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Technical Analysis Example:
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User: Analyze this PHP code for vulnerabilities: $sql = "SELECT * FROM users WHERE user = '" . $user . "'";
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nu11secur1tyAI: VULNERABILITY DETECTED: SQL Injection. Reason: Direct string concatenation. FIX: Implement Prepared Statements using mysqli::prepare() and bind_param().
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🧪 Development Context
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Architecture: 30B Parameter Evolution
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Developer Identity: nu11secur1ty
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Focus: Offensive & Defensive Security Research
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Framework: Platinum PEFT-Patched Trainer
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⚖️ Disclaimer
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This project is created strictly for educational purposes and legal security auditing. nu11secur1ty assumes no liability for any misuse or damages caused by the application of this model. Use with professional responsibility.
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"We don't just follow the evolution; we train it."
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Developed by nu11secur1ty
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