Installation

This guide will help you install PettingLLMs and its dependencies.

Prerequisites

Before installing PettingLLMs, ensure you have:

• Python 3.8+
• CUDA 11.8+ (for GPU support)
• Git

Quick Installation

The easiest way to install PettingLLMs is using the provided setup script:

git clone https://github.com/pettingllms-ai/PettingLLMs.git
cd PettingLLMs
bash setup.bash

This script will:

1. Create a virtual environment
2. Install all required dependencies
3. Set up the PettingLLMs package in development mode

Manual Installation

If you prefer to install manually, follow these steps:

1. Clone the Repository

git clone https://github.com/pettingllms-ai/PettingLLMs.git
cd PettingLLMs

2. Create Virtual Environment

python -m venv pettingllms_venv
source pettingllms_venv/bin/activate  # On Linux/Mac
# or
pettingllms_venv\Scripts\activate  # On Windows

3. Install Dependencies

For CUDA 12.8:

pip install -r requirements_venv_cu128.txt

For other CUDA versions:

pip install -r requirements_venv.txt

4. Install PettingLLMs

pip install -e .

Verify Installation

To verify that PettingLLMs is installed correctly:

python -c "import pettingllms; print('PettingLLMs installed successfully!')"

Docker Installation (Optional)

If you prefer using Docker, you can build a container with all dependencies:

# Coming soon

Troubleshooting

CUDA Issues

If you encounter CUDA-related errors:

1. Check your CUDA version: nvcc --version
2. Install the appropriate PyTorch version for your CUDA
3. Verify GPU is accessible: python -c "import torch; print(torch.cuda.is_available())"

Import Errors

If you get import errors:

1. Ensure the virtual environment is activated
2. Reinstall the package: pip install -e .
3. Check Python version compatibility

Dependency Conflicts

If you encounter dependency conflicts:

1. Try creating a fresh virtual environment
2. Update pip: pip install --upgrade pip
3. Install dependencies one at a time to identify conflicts

Next Steps

Once installation is complete, proceed to the Quick Start Guide to run your first training session.