mirror of
https://github.com/ollama/ollama.git
synced 2026-11-12 03:46:14 -06:00
Daniel HiltgenandGitHub
5e31438d5d
Replace the prerelease checkpoint path with Gradium's GA format, including default-voice import and speech conditioning. Set the 0.40.9 minimum, update the speech docs, and test import, inference setup, and rejection of the old checkpoint.
173 lines
2.8 KiB
Plaintext
173 lines
2.8 KiB
Plaintext
---
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title: CLI Reference
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---
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### Run a model
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```
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ollama run gemma4
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```
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### Launch integrations
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```
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ollama launch
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```
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Configure and launch external applications to use Ollama models. This provides an interactive way to set up and start integrations with supported apps.
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#### Supported integrations
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- **OpenCode** - Open-source coding assistant
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- **Claude Code** - Anthropic's agentic coding tool
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- **Codex** - OpenAI's coding assistant
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- **VS Code** - Microsoft's IDE with built-in AI chat
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- **Droid** - Factory's AI coding agent
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#### Examples
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Launch an integration interactively:
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```
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ollama launch
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```
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Launch a specific integration:
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```
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ollama launch claude
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```
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Launch with a specific model:
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```
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ollama launch claude --model qwen3.5
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```
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Configure without launching:
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```
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ollama launch droid --config
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```
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#### Multiline input
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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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#### Multimodal models
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```
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ollama run gemma4 "What's in this image? /Users/jmorgan/Desktop/smile.png"
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```
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### Generate embeddings
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```
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ollama run embeddinggemma "Hello world"
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```
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Output is a JSON array:
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```
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echo "Hello world" | ollama run nomic-embed-text
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```
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### Ask a decision model
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```
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ollama run nimble --ask "Is a refund being requested?" < ticket.txt
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ollama run nimble --ask "Which team should handle this?" \
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--choice billing="Payments and refunds" \
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--choice technical="Software problems" < ticket.txt
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ollama run nimble --ask "How urgent is this?" \
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--level "Routine" \
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--level "Soon" \
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--level "Immediate" < ticket.txt
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```
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The state is piped in or given after the model name, as text or JSON. Each `--ask` question is answered yes or no, unless it's followed by labels to choose from (`--choice`) or levels to score it on (`--level`). See [Decision](/capabilities/decision#ask-from-the-terminal).
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### Speak with a speech model
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```
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ollama run phonon "Hello from Ollama."
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ollama run phonon "Save this to a file." > speech.wav
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```
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The audio plays through your speakers, or is written as a WAV file when the output is redirected. Run it without text to speak each line you type. See [Speech](/capabilities/speech#speak-from-the-terminal).
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### Download a model
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```
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ollama pull gemma4
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```
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### Remove a model
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```
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ollama rm gemma4
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```
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### List models
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```
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ollama ls
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```
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### Sign in to Ollama
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```
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ollama signin
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```
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### Sign out of Ollama
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```
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ollama signout
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```
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### Create a customized model
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First, create a `Modelfile`
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```
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FROM gemma4
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SYSTEM """You are a happy cat."""
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```
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Then run `ollama create`:
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```
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ollama create -f Modelfile
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```
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### List running models
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```
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ollama ps
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```
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### Stop a running model
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```
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ollama stop gemma4
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```
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### Start Ollama
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```
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ollama serve
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```
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To view a list of environment variables that can be set run `ollama serve --help`
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