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Get up and running with large language models.
curl -fsSL https://ollama.com/install.sh | sh
ollama pull llama3
ollama run llama3
The official Ollama Docker image ollama/ollama
is available on Docker Hub.
To run and chat with Llama 3:
ollama run llama3
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 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:
Modelfile
, with a FROM
instruction with the local filepath to the model you want to import. FROM ./vicuna-33b.Q4_0.gguf
ollama create example -f Modelfile
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
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.
ollama create
is used to create a model from a Modelfile.
ollama create mymodel -f ./Modelfile
ollama pull llama3
This command can also be used to update a local model. Only the diff will be pulled.
ollama rm llama3
ollama cp llama3 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.
>>> 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 "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
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
Ollama has a REST API for running and managing models.
curl http://localhost:11434/api/generate -d '{
"model": "llama3",
"prompt":"Why is the sky blue?"
}'
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.