166 lines
5.1 KiB
Markdown
166 lines
5.1 KiB
Markdown
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<source media="(prefers-color-scheme: dark)" height="200px" srcset="https://github.com/jmorganca/ollama/assets/3325447/56ea1849-1284-4645-8970-956de6e51c3c">
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<img alt="logo" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
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# Ollama
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[](https://discord.gg/ollama)
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Run, create, and share large language models (LLMs).
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> Note: Ollama is in early preview. Please report any issues you find.
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## Download
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- [Download](https://ollama.ai/download) for macOS
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- Download for Windows and Linux (coming soon)
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- Build [from source](#building)
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## Quickstart
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To run and chat with [Llama 2](https://ai.meta.com/llama), the new model by Meta:
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```
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ollama run llama2
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```
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## Model library
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Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library "ollama model library")
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Here are some example open-source models that can be downloaded:
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| Model | Parameters | Size | Download |
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| ------------------------ | ---------- | ----- | ------------------------------- |
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| Llama2 | 7B | 3.8GB | `ollama pull llama2` |
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| Llama2 13B | 13B | 7.3GB | `ollama pull llama2:13b` |
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| Llama2 70B | 70B | 39GB | `ollama pull llama2:70b` |
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| Llama2 Uncensored | 7B | 3.8GB | `ollama pull llama2-uncensored` |
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| Orca Mini | 3B | 1.9GB | `ollama pull orca-mini` |
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| Vicuna | 7B | 3.8GB | `ollama pull vicuna` |
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| Nous-Hermes | 7B | 3.8GB | `ollama pull nous-hermes` |
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| Nous-Hermes 13B | 13B | 7.3GB | `ollama pull nous-hermes:13b` |
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| Wizard Vicuna Uncensored | 13B | 7.3GB | `ollama pull wizard-vicuna` |
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> 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.
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## Examples
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### Run a model
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```
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ollama run llama2
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>>> hi
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Hello! How can I help you today?
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```
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For multiline input, you can wrap text with `"""`:
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```
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>>> """Hello,
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... world!
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... """
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I'm a basic program that prints the famous "Hello, world!" message to the console.
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```
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### Create a custom model
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Pull a base model:
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```
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ollama pull llama2
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```
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> To update a model to the latest version, run `ollama pull llama2` again. The model will be updated (if necessary).
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Create a `Modelfile`:
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```
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FROM llama2
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# set the temperature to 1 [higher is more creative, lower is more coherent]
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PARAMETER temperature 1
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# set the system prompt
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SYSTEM """
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You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
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"""
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```
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Next, create and run the model:
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```
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ollama create mario -f ./Modelfile
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ollama run mario
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>>> hi
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Hello! It's your friend Mario.
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```
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For more examples, see the [examples](./examples) directory. For more information on creating a Modelfile, see the [Modelfile](./docs/modelfile.md) documentation.
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### Pull a model from the registry
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```
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ollama pull orca
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```
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### Listing local models
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```
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ollama list
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```
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## Model packages
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### Overview
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Ollama bundles model weights, configuration, and data into a single package, defined by a [Modelfile](./docs/modelfile.md).
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<picture>
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<source media="(prefers-color-scheme: dark)" height="480" srcset="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
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<img alt="logo" height="480" src="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
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</picture>
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## Building
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```
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go build .
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```
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To run it start the server:
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```
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./ollama serve &
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```
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Finally, run a model!
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```
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./ollama run llama2
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```
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## REST API
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> See the [API documentation](./docs/api.md) for all endpoints.
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Ollama has an API for running and managing models. For example to generate text from a model:
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```
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curl -X POST http://localhost:11434/api/generate -d '{
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"model": "llama2",
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"prompt":"Why is the sky blue?"
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}'
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```
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## Tools using Ollama
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- [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 a question-answering [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa).
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- [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.
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- [LiteLLM](https://github.com/BerriAI/litellm) a lightweight python package to simplify LLM API calls
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- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot) - interact with Ollama as a chatbot on Discord.
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- [Raycast Ollama](https://github.com/MassimilianoPasquini97/raycast_ollama) - Raycast extension to use Ollama for local llama inference on Raycast.
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- [Simple HTML UI for Ollama](https://github.com/rtcfirefly/ollama-ui)
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- [Emacs client](https://github.com/zweifisch/ollama) for Ollama
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