You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 
Jeffrey Morgan 463a8aa273
Create SECURITY.md
2 years ago
.github Bump Go patch version 2 years ago
api Add Metrics to `api\embed` response (#5709) 2 years ago
app upate to `llama3.1` elsewhere in repo (#6032) 2 years ago
auth prompt to display and add local ollama keys to account (#3717) 2 years ago
cmd Merge pull request #5895 from dhiltgen/sched_faq 2 years ago
convert convert: capture `head_dim` for mistral (#5818) 2 years ago
docs Merge pull request #5895 from dhiltgen/sched_faq 2 years ago
envconfig Remove no longer supported max vram var 2 years ago
examples Update and Fix example models (#6065) 2 years ago
format lint 2 years ago
gpu Ensure amd gpu nodes are numerically sorted 2 years ago
integration Add Metrics to `api\embed` response (#5709) 2 years ago
llm patch gemma support 2 years ago
macapp upate to `llama3.1` elsewhere in repo (#6032) 2 years ago
openai return tool calls finish reason for openai (#5995) 2 years ago
parser feat: add support for min_p (resolve #1142) (#1825) 2 years ago
progress lint 2 years ago
readline more lint 2 years ago
scripts Report better error on cuda unsupported os/arch 2 years ago
server Add Metrics to `api\embed` response (#5709) 2 years ago
template Merge pull request #5512 from ollama/mxyng/detect-stop 2 years ago
types types/model: remove knowledge of digest (#5500) 2 years ago
util/bufioutil llm: speed up gguf decoding by a lot (#5246) 2 years ago
version add version 3 years ago
.dockerignore add `macapp` to `.dockerignore` 2 years ago
.gitattributes Update .gitattributes 2 years ago
.gitignore ignore debug bin files 2 years ago
.gitmodules Init submodule with new path 3 years ago
.golangci.yaml gofmt, goimports 2 years ago
.prettierrc.json move .prettierrc.json to root 3 years ago
Dockerfile Bump Go patch version 2 years ago
LICENSE `proto` -> `ollama` 3 years ago
README.md Update README to include Firebase Genkit (#6083) 2 years ago
SECURITY.md Create SECURITY.md 2 years ago
go.mod update named templates 2 years ago
go.sum detect chat template from KV 2 years ago
main.go change `github.com/jmorganca/ollama` to `github.com/ollama/ollama` (#3347) 2 years ago

README.md

 ollama

Ollama

Discord

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

Quickstart

To run and chat with Llama 3.1:

ollama run llama3.1

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 3.1 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 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.

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 llama3.1 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.

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 llama3.1

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

Remove a model

ollama rm llama3.1

Copy a model

ollama cp llama3.1 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

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.

Pass the prompt as an argument

$ 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.

Show model information

ollama show llama3.1

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 llama3.1

REST API

Ollama has a REST API for running and managing models.

Generate a response

curl http://localhost:11434/api/generate -d '{
  "model": "llama3.1",
  "prompt":"Why is the sky blue?"
}'

Chat with a model

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.

Community Integrations

Web & Desktop

Terminal

Database

Package managers

Libraries

Mobile

Extensions & Plugins

Supported backends

  • llama.cpp project founded by Georgi Gerganov.