Get up and running with large language models.
curl -fsSL https://ollama.com/install.sh | sh
The official Ollama Docker image ollama/ollama is available on Docker Hub.
To run and chat with Llama 3.1:
ollama run llama3.1
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 3.1 | 8B | 4.7GB | ollama run llama3.1 |
| Llama 3.1 | 70B | 40GB | ollama run llama3.1:70b |
| Llama 3.1 | 405B | 231GB | ollama run llama3.1:405b |
| Phi 3 Mini | 3.8B | 2.3GB | ollama run phi3 |
| Phi 3 Medium | 14B | 7.9GB | ollama run phi3:medium |
| Gemma 2 | 2B | 1.6GB | ollama run gemma2:2b |
| Gemma 2 | 9B | 5.5GB | ollama run gemma2 |
| Gemma 2 | 27B | 16GB | ollama run gemma2:27b |
| 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.
Ollama supports importing GGUF models in the Modelfile:
-
Create a file named
Modelfile, with aFROMinstruction with the local filepath to the model you want to import.FROM ./vicuna-33b.Q4_0.gguf -
Create the model in Ollama
ollama create example -f Modelfile -
Run the model
ollama run example
See the guide on importing models for more information.
Models from the Ollama library can be customized with a prompt. For example, to customize the llama3.1 model:
ollama pull llama3.1
Create a Modelfile:
FROM llama3.1
# 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.
ollama create is used to create a model from a Modelfile.
ollama create mymodel -f ./Modelfile
ollama pull llama3.1
This command can also be used to update a local model. Only the diff will be pulled.
ollama rm llama3.1
ollama cp llama3.1 my-model
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.
ollama run llava "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.
$ ollama run llama3.1 "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.
ollama show llama3.1
ollama list
ollama serve is used when you want to start ollama without running the desktop application.
See the developer guide
Next, start the server:
./ollama serve
Finally, in a separate shell, run a model:
./ollama run llama3.1
Ollama has a REST API for running and managing models.
curl http://localhost:11434/api/generate -d '{
"model": "llama3.1",
"prompt":"Why is the sky blue?"
}'
curl http://localhost:11434/api/chat -d '{
"model": "llama3.1",
"messages": [
{ "role": "user", "content": "why is the sky blue?" }
]
}'
See the API documentation for all endpoints.
- 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)
- Ollama with Google Mesop (Mesop Chat Client implementation with Ollama)
- Kerlig AI (AI writing assistant for macOS)
- AI Studio
- Sidellama (browser-based LLM client)
- LLMStack (No-code multi-agent framework to build LLM agents and workflows)
- BoltAI for Mac (AI Chat Client for Mac)
- Harbor (Containerized LLM Toolkit with Ollama as default backend)
- 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
- Ollama eBook Summary
- MindsDB (Connects Ollama models with nearly 200 data platforms and apps)
- chromem-go with example
- LangChain and LangChain.js with example
- Firebase Genkit
- 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
- 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 Hugging Face)
- 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)
- llama.cpp project founded by Georgi Gerganov.