Ollama makes it easy to run and experiment with large language models locally. Get started in minutes, no cloud required.
Ollama Key Features
Easy Setup
Download and install Ollama, and you're ready to go. No complex configurations or dependencies required.
Run Models Locally
Ollama allows you to run large language models directly on your machine, ensuring data privacy and low latency.
Model Library
Access a growing library of pre-trained models, including Llama 2, Mistral, and more.
Customization
Easily modify and customize models to suit your specific needs.
Cross-Platform Compatibility
Ollama is available for macOS and Linux, with Windows support coming soon.
How Ollama Works
Ollama provides a command-line interface (CLI) for managing and running models. Simply download the desired model, and Ollama takes care of the rest, including managing dependencies and optimizing performance.
Ollama Benefits
Data Privacy
Run models locally and keep your data private and secure.
Low Latency
Eliminate network latency by running models directly on your machine.
Offline Access
Continue working even without an internet connection.
Cost Efficiency
Avoid cloud computing costs by running models locally.
Experimentation
Quickly prototype and experiment with different models and configurations.
Ollama Use Cases
Local Development
Develop and test applications that use large language models without relying on external APIs.
Research
Experiment with different models and fine-tune them for specific tasks.
Education
Learn about large language models and how they work by running them locally.
Ollama FAQs
What models are supported?
Ollama supports a growing library of pre-trained models, including Llama 2, Mistral, and more. Check the official documentation for the latest list.
What platforms are supported?
Ollama is currently available for macOS and Linux, with Windows support coming soon.
How do I customize a model?
You can customize a model by modifying its configuration file or by fine-tuning it with your own data.
Who Should Use Ollama
Developers, researchers, and enthusiasts who want to experiment with large language models locally. Perfect for both beginners and experienced users.
