Run, create, and share large language models (LLMs).

Note: Ollama is in early preview. Please report any issues you find.

• Download for macOS
• Download for Windows and Linux (coming soon)
• Build from source

To run and chat with Llama 2, the new model by Meta:

ollama run llama2

Ollama supports a list of open-source models available on ollama.ai/library

Here are some example open-source models that can be downloaded:

Note: You should have at least 8 GB of RAM to run the 3B models, 16 GB to run the 7B models, and 32 GB to run the 13B models.

ollama run llama2
>>> hi
Hello! How can I help you today?

For multiline input, you can wrap text with """:

>>> """Hello,
... world!
... """
I'm a basic program that prints the famous "Hello, world!" message to the console.

Pull a base model:

ollama pull llama2

To update a model to the latest version, run ollama pull llama2 again. The model will be updated (if necessary).

Create a Modelfile:

FROM llama2

# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1

# set the system prompt
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""

Next, create and run the model:

ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.

For more examples, see the examples directory. For more information on creating a Modelfile, see the Modelfile documentation.

ollama pull orca-mini

ollama list

Ollama bundles model weights, configuration, and data into a single package, defined by a Modelfile.

You will also need a C/C++ compiler such as GCC for MacOS and Linux or Mingw-w64 GCC for Windows.

go build .

To run it start the server:

./ollama serve &

Finally, run a model!

./ollama run llama2

See the API documentation for all endpoints.

Ollama has an API for running and managing models. For example to generate text from a model:

curl -X POST http://localhost:11434/api/generate -d '{
  "model": "llama2",
  "prompt":"Why is the sky blue?"
}'

• LangChain and LangChain.js with a question-answering example.
• Continue - embeds Ollama inside Visual Studio Code. The extension lets you highlight code to add to the prompt, ask questions in the sidebar, and generate code inline.
• LiteLLM a lightweight python package to simplify LLM API calls
• Discord AI Bot - interact with Ollama as a chatbot on Discord.
• Raycast Ollama - Raycast extension to use Ollama for local llama inference on Raycast.
• Simple HTML UI for Ollama
• Emacs client for Ollama