Installation
RamaLama can be installed on multiple platforms using various methods. Choose the installation method that best fits your environment.
Quick Install
Universal Install Script (Linux and macOS)
The easiest way to install RamaLama is using the universal install script:
curl -fsSL https://ramalama.ai/install.sh | bash
This script will automatically detect your system and install RamaLama with the appropriate method.
Platform-Specific Installation
Fedora
On Fedora systems, you can install RamaLama directly from the official repositories:
sudo dnf install python3-ramalama
PyPI (All Platforms)
RamaLama is available on PyPI and can be installed using pip:
pip install ramalama
Optional Components
MLX Runtime (macOS with Apple Silicon)
For macOS users with Apple Silicon hardware (M1, M2, M3, or later), you can install the MLX runtime for enhanced performance:
# Using uv (recommended)
uv pip install mlx-lm
# Or using pip
pip install mlx-lm
The MLX runtime is specifically designed for Apple Silicon Macs and provides optimized AI model inference. To use MLX, you'll need to run RamaLama with the --nocontainer
option.
Verify Installation
After installation, verify that RamaLama is working correctly:
ramalama version
You should see output similar to:
ramalama version 0.11.1
Next Steps
Once RamaLama is installed, you can:
- Pull your first model:
ramalama pull ollama://tinyllama
- Run a model:
ramalama run ollama://tinyllama
- Explore available commands:
ramalama --help
For detailed usage instructions, see the Commands section.
Platform-Specific Setup
After installation, you may need additional platform-specific configuration:
- NVIDIA GPUs: See CUDA Setup
- macOS: See macOS Setup
- Ascend NPUs: See CANN Setup