Instructions to use hayulalab/Averroes-7B-v2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use hayulalab/Averroes-7B-v2-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hayulalab/Averroes-7B-v2-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf hayulalab/Averroes-7B-v2-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hayulalab/Averroes-7B-v2-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf hayulalab/Averroes-7B-v2-GGUF: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 hayulalab/Averroes-7B-v2-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf hayulalab/Averroes-7B-v2-GGUF: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 hayulalab/Averroes-7B-v2-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hayulalab/Averroes-7B-v2-GGUF:F16

Use Docker

docker model run hf.co/hayulalab/Averroes-7B-v2-GGUF:F16

LM Studio
Jan
Ollama
How to use hayulalab/Averroes-7B-v2-GGUF with Ollama:
```
ollama run hf.co/hayulalab/Averroes-7B-v2-GGUF:F16
```

Unsloth Studio

How to use hayulalab/Averroes-7B-v2-GGUF 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 hayulalab/Averroes-7B-v2-GGUF 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 hayulalab/Averroes-7B-v2-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for hayulalab/Averroes-7B-v2-GGUF to start chatting

How to use hayulalab/Averroes-7B-v2-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hayulalab/Averroes-7B-v2-GGUF:F16

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": "hayulalab/Averroes-7B-v2-GGUF:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use hayulalab/Averroes-7B-v2-GGUF with Docker Model Runner:
```
docker model run hf.co/hayulalab/Averroes-7B-v2-GGUF:F16
```

Lemonade

How to use hayulalab/Averroes-7B-v2-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hayulalab/Averroes-7B-v2-GGUF:F16

Run and chat with the model

lemonade run user.Averroes-7B-v2-GGUF-F16

List all available models

lemonade list

Hermes Agent

How to use hayulalab/Averroes-7B-v2-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hayulalab/Averroes-7B-v2-GGUF:F16

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 hayulalab/Averroes-7B-v2-GGUF:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use hayulalab/Averroes-7B-v2-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf hayulalab/Averroes-7B-v2-GGUF:F16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "hayulalab/Averroes-7B-v2-GGUF:F16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

🌐 Part of Hayula Agent OS

91 Agents. 4 Devices. 8 Frameworks. Zero Cloud.

license: other license_name: Hayula Research License v1.0 license_link: https://hayula.xyz/license language: - en - ar tags: - gguf - quantized - averroes - arabic - llm

Averroes-7B-v2 GGUF

This repository contains GGUF quantized versions of Averroes-7B-v2, a bilingual Arabic-English language model fine-tuned from Llama-3.1-8B.

Available Files

File	Size	Description
averroes-7b-q4_k_m.gguf	4.68 GB	Q4_K_M quantized (recommended)

Usage with llama.cpp

Build llama.cpp and run: ./llama-cli -m averroes-7b-q4_k_m.gguf -n 512 -p "Your prompt here"

Usage with Ollama

ollama run hf.co/hayulalab/Averroes-7B-v2-GGUF:q4_k_m

Part of the Hayula Agent OS ecosystem — 91 open-source AI agents across 4 devices, 8 frameworks. Your hardware. Your data. Zero cloud.

License

This model is licensed under the Hayula Research License v1.0.

Permissions

✅ Research Use: Free to use, modify, and distribute for academic and non-commercial research
✅ Attribution Required: Credit "Hayula Lab" and link to the original model page

Restrictions

❌ No Commercial Use: You may NOT use this model or derivatives for commercial purposes without explicit written permission from Hayula Labs
❌ No Competing Services: You may NOT offer this model (or derivatives) as a hosted service competitive to Hayula products
❌ No Redistribution Under Different License: You may NOT relicense this model or derivatives under a more permissive license

Commercial Licensing

For commercial use, research collaborations, or enterprise licensing, contact:

Email: Hayulalabs@gmail.com
Website: https://hayula.xyz

Citation

If you use this model in your research, please cite:

@misc{hayula-lab,
  author = {Hayula Lab},
  title = {Hayula Agent OS — Open Source AI Agent Ecosystem},
  year = {2026},
  publisher = {HuggingFace},
  url = {https://hayula.xyz}
}

_{Built with ❤️ by Hayula Labs}

Downloads last month: 21

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

4-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support