README.md

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# Ollama

[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)

> [!NOTE]
> Ollama is in early preview. Please report any issues you find.

Run, create, and share large language models (LLMs).

## Download

- [Download](https://ollama.ai/download) for macOS
- Download for Windows and Linux (coming soon)
- Build [from source](#building)

## Quickstart

To run and chat with [Llama 2](https://ai.meta.com/llama), 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?
```

### 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](./examples) directory.

For more information on creating a Modelfile, see the [Modelfile](./docs/modelfile.md) 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](./docs/modelfile.md).

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## Building

```
go build .
```

To run it start the server:

```
./ollama serve &
```

Finally, run a model!

```
./ollama run llama2
```

## REST API

> See the [API documentation](./docs/api.md) 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](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa) integration - Set up all local, JS-based retrival + QA over docs in 5 minutes.
- [Continue](https://github.com/continuedev/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.
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot) - interact with Ollama as a chatbot on Discord.
- [Raycast Ollama](https://github.com/MassimilianoPasquini97/raycast_ollama) - Raycast extension to use Ollama for local llama inference on Raycast.
- [Simple HTML UI for Ollama](https://github.com/rtcfirefly/ollama-ui)