Ollama

What is Ollama ?

Ollama is LLMs Backend that allow you to get up and running with large language models locally.

Run Llama 2, Code Llama, and other models. Customize and create your own.

Install Ollama

macOS

Download the latest release on Github :

Download

Linux & WSL2

curl https://ollama.ai/install.sh | sh

Docker

The official Ollama Docker image ollama/ollama is available on Docker Hub.

Quickstart

To run and chat with Llama 2:

ollama run llama2

Manual Install on Linux

Download the ollama binary

Ollama is distributed as a self-contained binary. Download it to a directory in your PATH:

sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama

sudo chmod +x /usr/bin/ollama

Adding Ollama as a startup service (recommended)

Create a user for Ollama:

sudo useradd -r -s /bin/false -m -d /usr/share/ollama ollama

Create a service file in /etc/systemd/system/ollama.service :

[Unit]

Description=Ollama Service

After=network-online.target

[Service]

ExecStart=/usr/bin/ollama serve

User=ollama

Group=ollama

Restart=always

RestartSec=3

[Install]

WantedBy=default.target

Then start the service:

sudo systemctl daemon-reload

sudo systemctl enable ollama

Install CUDA drivers (optional – for Nvidia GPUs)

Download and install CUDA.

Verify that the drivers are installed by running the following command, which should print details about your GPU:

nvidia-smi

Start Ollama

Start Ollama using systemd :

sudo systemctl start ollama

Update Ollama

Update ollama by running the install script again:

curl https://ollama.ai/install.sh | sh

Or by downloading the ollama binary:

sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama

sudo chmod +x /usr/bin/ollama

Viewing logs

To view logs of Ollama running as a startup service, run:

journalctl -u ollama

Uninstall Ollama

Remove the ollama service:

sudo systemctl stop ollama

sudo systemctl disable ollama

sudo rm /etc/systemd/system/ollama.service

Remove the ollama binary from your bin directory (either /usr/local/bin , /usr/bin , or /bin ):

sudo rm $(which ollama)

Remove the downloaded models and Ollama service user:

sudo rm -r /usr/share/ollama

sudo userdel ollama

Model library

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 available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.

Customize a model

Import from GGUF

Ollama supports importing GGUF models in the Modelfile:

1. Create a file named Modelfile, with a FROM instruction with the local filepath to the model you want to import.

   FROM ./vicuna-33b.Q4_0.gguf

1. Create the model in Ollama

   ollama create example -f Modelfile

1. Run the model

   ollama run example

Import from PyTorch or Safetensors

See the guide on importing models for more information.

Customize a prompt

Models from the Ollama library can be customized with a prompt. For example, to customize the llama2 model:

ollama pull llama2

Create a Modelfile :

FROM llama2

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

PARAMETER temperature 1

# set the system message

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 working with a Modelfile, see the Modelfile documentation.

CLI Reference

Create a model

ollama create is used to create a model from a Modelfile.

ollama create mymodel -f ./Modelfile

Pull a model

ollama pull llama2

This command can also be used to update a local model. Only the diff will be pulled.

Remove a model

ollama rm llama2

Copy a model

ollama cp llama2 my-llama2

Multiline input

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.

Multimodal models

>>> What's in this image? /Users/jmorgan/Desktop/smile.png

The image features a yellow smiley face, which is likely the central focus of the picture.

Pass in prompt as arguments

$ ollama run llama2 "Summarize this file: $(cat README.md)"

 Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.

List models on your computer

ollama list

Start Ollama

ollama serve is used when you want to start ollama without running the desktop application.

Building

Install cmake and go :

brew install cmake go

Then generate dependencies:

go generate ./...

```sh

Then build the binary:

```sh

go build .

More detailed instructions can be found in the developer guide

Running local builds

Next, start the server:

./ollama serve

Finally, in a separate shell, run a model:

./ollama run llama2

REST API

Ollama has a REST API for running and managing models.

Generate a response

curl http://localhost:11434/api/generate -d '{

  "model": "llama2",

  "prompt":"Why is the sky blue?"

}'

Chat with a model

curl http://localhost:11434/api/chat -d '{

  "model": "mistral",

  "messages": [

    { "role": "user", "content": "why is the sky blue?" }

  ]

}'

See the API documentation for all endpoints.

Community Integrations

Web & Desktop

• Bionic GPT

• HTML UI

• Chatbot UI

• Typescript UI

• Minimalistic React UI for Ollama Models

• Web UI

• Ollamac

• big-AGI

• Cheshire Cat assistant framework

• Amica

• chatd

• Ollama-SwiftUI

Terminal

• oterm

• Ellama Emacs client

• Emacs client

• gen.nvim

• ollama.nvim

• ogpt.nvim

• gptel Emacs client

• Oatmeal

• cmdh

Database

• MindsDB

Package managers

• Pacman

Libraries

• LangChain and LangChain.js with example

• LangChainGo with example

• LlamaIndex

• LiteLLM

• OllamaSharp for . NET

• Ollama-rs for Rust

• Ollama4j for Java

• ModelFusion Typescript Library

• OllamaKit for Swift

• Ollama for Dart

• Ollama for Laravel

• LangChainDart

Mobile

• Enchanted

• Maid

Extensions & Plugins

• Raycast extension

• Discollama (Discord bot inside the Ollama discord channel)

• Continue

• Obsidian Ollama plugin

• Logseq Ollama plugin

• Dagger Chatbot

• Discord AI Bot

• Ollama Telegram Bot

• Hass Ollama Conversation

• Rivet plugin

• Llama Coder (Copilot alternative using Ollama)

• Obsidian BMO Chatbot plugin