Instructions to use saberbx/XO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use saberbx/XO with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="saberbx/XO", filename="unsloth.F16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use saberbx/XO with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf saberbx/XO:F16 # Run inference directly in the terminal: llama-cli -hf saberbx/XO:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf saberbx/XO:F16 # Run inference directly in the terminal: llama-cli -hf saberbx/XO:F16
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 saberbx/XO:F16 # Run inference directly in the terminal: ./llama-cli -hf saberbx/XO:F16
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 saberbx/XO:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf saberbx/XO:F16
Use Docker
docker model run hf.co/saberbx/XO:F16
- LM Studio
- Jan
- Ollama
How to use saberbx/XO with Ollama:
ollama run hf.co/saberbx/XO:F16
- Unsloth Studio new
How to use saberbx/XO 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 saberbx/XO 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 saberbx/XO to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for saberbx/XO to start chatting
- Docker Model Runner
How to use saberbx/XO with Docker Model Runner:
docker model run hf.co/saberbx/XO:F16
- Lemonade
How to use saberbx/XO with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull saberbx/XO:F16
Run and chat with the model
lemonade run user.XO-F16
List all available models
lemonade list
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 saberbx/XO to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for saberbx/XO to start chattingXO: A Llama 3.2 3B, Unsloth-Trained Cybersecurity Expert
Model Description
XO is an instruction-fine-tuned model based on unsloth/llama-3.2-3b-instruct-nb-bnb-4bit. It is engineered to be a lightweight, efficient, and highly specialized AI assistant for cybersecurity tasks. Its small size makes it ideal for local deployment on consumer-grade hardware using tools like Ollama or LM Studio.
The model was fine-tuned using the Unsloth framework, ensuring maximum performance and minimal resource consumption from the 3B parameter architecture. This version of XO is trained on a focused, foundational dataset to provide core cybersecurity knowledge and a consistent persona in English.
Model Details
- Model Type: Fine-tuned Causal Language Model
- Base Model: unsloth/llama-3.2-3b-instruct-nb-bnb-4bit
- Training Framework: Unsloth ๐
- Training Data: The model was trained on the foundational, English-only
saberbx/X-mini-datasets. This dataset includes:- Core knowledge adapted from the "Payloads All The Things" repository.
- An introductory Chain-of-Thought module for basic reasoning.
- A persona module to define its identity as "XO," created by "Saber."
- Important Note: This model is NOT trained on the advanced, bilingual dataset and does NOT include advanced mathematical reasoning capabilities.
Capabilities & Intended Use
XO is designed to be a reliable local assistant for day-to-day cybersecurity tasks. Its primary capabilities include:
- ๐ป Optimized for Local Deployment: Its 3B parameter size allows it to run smoothly on machines with limited VRAM, making powerful AI accessible.
- ๐ก๏ธ Core Cybersecurity Knowledge: Acts as an interactive encyclopedia of "Payloads All The Things," providing quick access to common payloads, commands, and checklists.
- ๐ง Foundational Reasoning: Capable of performing basic step-by-step analysis for common cybersecurity problems based on its Chain-of-Thought training.
- ๐ค Consistent Persona: Always responds as "XO," the AI assistant created by "Saber," providing a consistent and predictable user experience.
Limitations and Ethical Considerations
- โ ๏ธ For Ethical & Defensive Use Only: This model is designed to empower cybersecurity professionals. Any use for malicious or illegal activities is strictly prohibited.
- Limited Scope: This model's knowledge is based on its foundational English training data. It does not possess advanced or multilingual capabilities.
- Potential for Hallucinations: Like all LLMs, XO can generate incorrect information. Always verify critical information with a human expert.
- Bias Warning: The model may reflect biases from its training data.
Citation
If you use this model in your research or project, please cite our work:
@misc{saber_xo_3b_2024,
author = {Saber},
title = {XO: A Llama 3.2 3B, Unsloth-Trained Cybersecurity Expert},
year = {2025},
publisher = {Hugging Face},
journal = {Hugging Face repository},
howpublished = {\url{https://huggingface.co/saberbx/XO}}
}
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Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for saberbx/XO to start chatting