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Co-authored-by: default avatarJeffrey Morgan <jmorganca@gmail.com>
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README.md
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[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
Run, create, and share large language models (LLMs).
Get up and running with large language models locally.
> Note: Ollama is in early preview. Please report any issues you find.
### macOS
## Download
[Download](https://ollama.ai/download/Ollama-darwin.zip)
- [Download](https://ollama.ai/download) for macOS
- Download for Windows and Linux (coming soon)
- Build [from source](#building)
### Linux & WSL2
```
curl https://ollama.ai/install.sh | sh
```
[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
### Windows
coming soon
## Quickstart
To run and chat with [Llama 2](https://ai.meta.com/llama), the new model by Meta:
To run and chat with [Llama 2](https://ollama.ai/library/llama2):
```
ollama run llama2
......@@ -29,87 +37,49 @@ ollama run llama2
## Model library
Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library 'ollama model library')
Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library "ollama model library")
Here are some example open-source models that can be downloaded:
| 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` |
| Code Llama | 7B | 3.8GB | `ollama pull codellama` |
| Orca Mini | 3B | 1.9GB | `ollama pull orca-mini` |
| Vicuna | 7B | 3.8GB | `ollama pull vicuna` |
| Nous-Hermes | 7B | 3.8GB | `ollama pull nous-hermes` |
| Nous-Hermes 13B | 13B | 7.3GB | `ollama pull nous-hermes:13b` |
| Wizard Vicuna Uncensored | 13B | 7.3GB | `ollama pull wizard-vicuna` |
| Model | Parameters | Size | Download |
| ------------------ | ---------- | ----- | ------------------------------ |
| Llama 2 | 7B | 3.8GB | `ollama run llama2` |
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| Llama 2 13B | 13B | 7.3GB | `ollama run llama2:13b` |
| Llama 2 70B | 70B | 39GB | `ollama run llama2:70b` |
| Orca Mini | 3B | 1.9GB | `ollama run orca-mini` |
| Vicuna | 7B | 3.8GB | `ollama run 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
## Customize your own model
### Pull a public model
### Import from GGUF or GGML
```
ollama pull llama2
```
Ollama supports importing GGUF and GGML file formats in the Modelfile. This means if you have a model that is not in the Ollama library, you can create it, iterate on it, and upload it to the Ollama library to share with others when you are ready.
> This command can also be used to update a local model. Only updated changes will be pulled.
1. Create a file named Modelfile, and add a `FROM` instruction with the local filepath to the model you want to import.
### Run a model interactively
```
FROM ./vicuna-33b.Q4_0.gguf
```
```
ollama run llama2
>>> hi
Hello! How can I help you today?
```
3. Create the model in Ollama
For multiline input, you can wrap text with `"""`:
```
ollama create name -f path_to_modelfile
```
```
>>> """Hello,
... world!
... """
I'm a basic program that prints the famous "Hello, world!" message to the console.
```
### Run a model non-interactively
```
$ ollama run llama2 'tell me a joke'
Sure! Here's a quick one:
Why did the scarecrow win an award? Because he was outstanding in his field!
```
```
$ cat <<EOF >prompts.txt
tell me a joke about llamas
tell me another one
EOF
$ ollama run llama2 <prompts.txt
>>> tell me a joke about llamas
Why did the llama refuse to play hide-and-seek?
nobody likes to be hided!
5. Run the model
>>> tell me another one
Sure, here's another one:
```
ollama run name
```
Why did the llama go to the bar?
To have a hay-often good time!
```
### Customize a prompt
### Run a model on contents of a text file
```
$ ollama run llama2 "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.
```
### Customize a model
Pull a base model:
Models from the Ollama library can be customized with a prompt. The example
```
ollama pull llama2
......@@ -138,30 +108,61 @@ ollama run mario
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.
For more examples, see the [examples](./examples) directory. For more information on working with a Modelfile, see the [Modelfile](./docs/modelfile.md) documentation.
## CLI Reference
### Create a model
`ollama create` is used to create a model from a Modelfile.
### Listing local models
### Pull a model
```
ollama list
ollama pull llama2
```
### Removing local models
> This command can also be used to update a local model. Only the diff will be pulled.
### Remove a model
```
ollama rm llama2
```
## Model packages
### Copy a model
```
ollama cp llama2 my-llama2
```
### 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.
```
### Pass in prompt as arguments
```
$ ollama run llama2 "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.
```
### List models on your computer
### Overview
```
ollama list
```
Ollama bundles model weights, configurations, and data into a single package, defined by a [Modelfile](./docs/modelfile.md).
### Start Ollama
<picture>
<source media="(prefers-color-scheme: dark)" height="480" srcset="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
<img alt="logo" height="480" src="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
</picture>
`ollama serve` is used when you want to start ollama without running the desktop application.
## Building
......@@ -204,19 +205,18 @@ curl -X POST http://localhost:11434/api/generate -d '{
}'
```
## Community Projects using Ollama
| Project | Description |
| -------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| [LangChain][1] and [LangChain.js][2] | Also, there is a question-answering [example][3]. |
| [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. |
| [LiteLLM](https://github.com/BerriAI/litellm) | Lightweight Python package to simplify LLM API calls. |
| [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](https://github.com/rtcfirefly/ollama-ui) | Also, there is a Chrome extension. |
| [Ollama-GUI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file) | 🖥️ Mac Chat Interface ⚡️ |
| [Emacs client](https://github.com/zweifisch/ollama) | |
[1]: https://python.langchain.com/docs/integrations/llms/ollama
[2]: https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama
[3]: https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa
## Community Integrations
- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
- [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama)
- [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel)
- [Continue](https://github.com/continuedev/continue)
- [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
- [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
- [Dumbar](https://github.com/JerrySievert/Dumbar)
- [Emacs client](https://github.com/zweifisch/ollama)
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