e9a9580bdd
- re-use previously evaluated embeddings when possible - change embeddings digest identifier to be based on model name and embedded file path |
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api | ||
app | ||
cmd | ||
docs | ||
examples | ||
format | ||
llm | ||
parser | ||
progressbar | ||
scripts | ||
server | ||
vector | ||
.dockerignore | ||
.gitignore | ||
.prettierrc.json | ||
Dockerfile | ||
go.mod | ||
go.sum | ||
LICENSE | ||
main.go | ||
README.md |
Ollama
Run, create, and share large language models (LLMs).
Note: Ollama is in early preview. Please report any issues you find.
Download
- Download for macOS
- Download for Windows and Linux (coming soon)
- Build from source
Quickstart
To run and chat with Llama 2, the new model by Meta:
ollama run llama2
Model library
ollama
includes a library of open-source models:
Model | Parameters | Size | Download |
---|---|---|---|
Llama2 | 7B | 3.8GB | ollama pull llama2 |
Llama2 13B | 13B | 7.3GB | ollama pull llama2:13b |
Llama2 70B | 70B | 39GB | ollama pull llama2:70b |
Llama2 Uncensored | 7B | 3.8GB | ollama pull llama2-uncensored |
Orca Mini | 3B | 1.9GB | ollama pull orca |
Vicuna | 7B | 3.8GB | ollama pull vicuna |
Nous-Hermes | 13B | 7.3GB | ollama pull nous-hermes |
Wizard Vicuna Uncensored | 13B | 7.3GB | ollama pull wizard-vicuna |
Note: You should have at least 8 GB of RAM to run the 3B models, 16 GB to run the 7B models, and 32 GB to run the 13B models.
Examples
Run a model
ollama run llama2
>>> hi
Hello! How can I help you today?
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.
Create a custom model
Pull a base model:
ollama pull llama2
To update a model to the latest version, run
ollama pull llama2
again. The model will be updated (if necessary).
Create a Modelfile
:
FROM llama2
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# set the system prompt
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 creating a Modelfile, see the Modelfile documentation.
Pull a model from the registry
ollama pull orca
Listing local models
ollama list
Model packages
Overview
Ollama bundles model weights, configuration, and data into a single package, defined by a Modelfile.
Building
go build .
To run it start the server:
./ollama serve &
Finally, run a model!
./ollama run llama2
REST API
See the API documentation for all endpoints.
Ollama has an API for running and managing models. For example to generate text from a model:
curl -X POST http://localhost:11434/api/generate -d '{
"model": "llama2",
"prompt":"Why is the sky blue?"
}'
Tools using Ollama
- LangChain and LangChain.js with a question-answering example.
- Continue - embeds Ollama inside Visual Studio Code. The extension lets you highlight code to add to the prompt, ask questions in the sidebar, and generate code inline.
- LiteLLM a lightweight python package to simplify LLM API calls
- Discord AI Bot - interact with Ollama as a chatbot on Discord.
- Raycast Ollama - Raycast extension to use Ollama for local llama inference on Raycast.
- Simple HTML UI for Ollama
- Emacs client for Ollama