Ollama

Get up and running with large language models.

macOS

Download

Windows preview

Download

Linux

curl -fsSL https://ollama.com/install.sh | sh

Manual install instructions

Docker

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

Libraries

• ollama-python
• ollama-js

Quickstart

To run and chat with Llama 3:

ollama run llama3

Model library

Ollama supports a list of models available on ollama.com/library

Here are some example models that can be downloaded:

Model	Parameters	Size	Download
Llama 3	8B	4.7GB	ollama run llama3
Llama 3	70B	40GB	ollama run llama3:70b
Phi 3 Mini	3.8B	2.3GB	ollama run phi3
Phi 3 Medium	14B	7.9GB	ollama run phi3:medium
Gemma	2B	1.4GB	ollama run gemma:2b
Gemma	7B	4.8GB	ollama run gemma:7b
Mistral	7B	4.1GB	ollama run mistral
Moondream 2	1.4B	829MB	ollama run moondream
Neural Chat	7B	4.1GB	ollama run neural-chat
Starling	7B	4.1GB	ollama run starling-lm
Code Llama	7B	3.8GB	ollama run codellama
Llama 2 Uncensored	7B	3.8GB	ollama run llama2-uncensored
LLaVA	7B	4.5GB	ollama run llava
Solar	10.7B	6.1GB	ollama run solar

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
   

2. Create the model in Ollama

   ollama create example -f Modelfile
   

3. 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 llama3 model:

ollama pull llama3

Create a Modelfile:

FROM llama3

# 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 llama3

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

Remove a model

ollama rm llama3

Copy a model

ollama cp llama3 my-model

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 the prompt as an argument

$ ollama run llama3 "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.

Show model information

ollama show llama3

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

See the developer guide

Running local builds

Next, start the server:

./ollama serve

Finally, in a separate shell, run a model:

./ollama run llama3

REST API

Ollama has a REST API for running and managing models.

Generate a response

curl http://localhost:11434/api/generate -d '{
  "model": "llama3",
  "prompt":"Why is the sky blue?"
}'

Chat with a model

curl http://localhost:11434/api/chat -d '{
  "model": "llama3",
  "messages": [
    { "role": "user", "content": "why is the sky blue?" }
  ]
}'

See the API documentation for all endpoints.

Community Integrations

Web & Desktop

• Open WebUI
• Enchanted (macOS native)
• Hollama
• Lollms-Webui
• LibreChat
• Bionic GPT
• HTML UI
• Saddle
• Chatbot UI
• Chatbot UI v2
• Typescript UI
• Minimalistic React UI for Ollama Models
• Ollamac
• big-AGI
• Cheshire Cat assistant framework
• Amica
• chatd
• Ollama-SwiftUI
• Dify.AI
• MindMac
• NextJS Web Interface for Ollama
• Msty
• Chatbox
• WinForm Ollama Copilot
• NextChat with Get Started Doc
• Alpaca WebUI
• OllamaGUI
• OpenAOE
• Odin Runes
• LLM-X (Progressive Web App)
• AnythingLLM (Docker + MacOs/Windows/Linux native app)
• Ollama Basic Chat: Uses HyperDiv Reactive UI
• Ollama-chats RPG
• QA-Pilot (Chat with Code Repository)
• ChatOllama (Open Source Chatbot based on Ollama with Knowledge Bases)
• CRAG Ollama Chat (Simple Web Search with Corrective RAG)
• RAGFlow (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
• StreamDeploy (LLM Application Scaffold)
• chat (chat web app for teams)
• Lobe Chat with Integrating Doc
• Ollama RAG Chatbot (Local Chat with multiple PDFs using Ollama and RAG)
• BrainSoup (Flexible native client with RAG & multi-agent automation)
• macai (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
• Olpaka (User-friendly Flutter Web App for Ollama)
• OllamaSpring (Ollama Client for macOS)
• LLocal.in (Easy to use Electron Desktop Client for Ollama)

Terminal

• oterm
• Ellama Emacs client
• Emacs client
• gen.nvim
• ollama.nvim
• ollero.nvim
• ollama-chat.nvim
• ogpt.nvim
• gptel Emacs client
• Oatmeal
• cmdh
• ooo
• shell-pilot
• tenere
• llm-ollama for Datasette's LLM CLI.
• typechat-cli
• ShellOracle
• tlm
• podman-ollama
• gollama

Database

• MindsDB (Connects Ollama models with nearly 200 data platforms and apps)
• chromem-go with example

Package managers

• Pacman
• Helm Chart
• Guix channel

Libraries

• LangChain and LangChain.js with example
• LangChainGo with example
• LangChain4j with example
• LangChainRust with example
• LlamaIndex
• LiteLLM
• OllamaSharp for .NET
• Ollama for Ruby
• Ollama-rs for Rust
• Ollama-hpp for C++
• Ollama4j for Java
• ModelFusion Typescript Library
• OllamaKit for Swift
• Ollama for Dart
• Ollama for Laravel
• LangChainDart
• Semantic Kernel - Python
• Haystack
• Elixir LangChain
• Ollama for R - rollama
• Ollama for R - ollama-r
• Ollama-ex for Elixir
• Ollama Connector for SAP ABAP
• Testcontainers
• Portkey
• PromptingTools.jl with an example
• LlamaScript

Mobile

• Enchanted
• Maid

Extensions & Plugins

• Raycast extension
• Discollama (Discord bot inside the Ollama discord channel)
• Continue
• Obsidian Ollama plugin
• Logseq Ollama plugin
• NotesOllama (Apple Notes Ollama plugin)
• Dagger Chatbot
• Discord AI Bot
• Ollama Telegram Bot
• Hass Ollama Conversation
• Rivet plugin
• Obsidian BMO Chatbot plugin
• Cliobot (Telegram bot with Ollama support)
• Copilot for Obsidian plugin
• Obsidian Local GPT plugin
• Open Interpreter
• Llama Coder (Copilot alternative using Ollama)
• Ollama Copilot (Proxy that allows you to use ollama as a copilot like Github copilot)
• twinny (Copilot and Copilot chat alternative using Ollama)
• Wingman-AI (Copilot code and chat alternative using Ollama and HuggingFace)
• Page Assist (Chrome Extension)
• AI Telegram Bot (Telegram bot using Ollama in backend)
• AI ST Completion (Sublime Text 4 AI assistant plugin with Ollama support)
• Discord-Ollama Chat Bot (Generalized TypeScript Discord Bot w/ Tuning Documentation)
• Discord AI chat/moderation bot Chat/moderation bot written in python. Uses Ollama to create personalities.
• Headless Ollama (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)

Supported backends

• llama.cpp project founded by Georgi Gerganov.