Ollama: Difference between revisions
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== Setup == | == Setup == | ||
You can add Ollama in two ways to your system configuration. | |||
As a standalone package: | |||
<syntaxhighlight lang="nix"> | |||
environment.systemPackages = [ pkgs.ollama ]; | |||
</syntaxhighlight> | |||
As a systemd service: | |||
<syntaxhighlight lang="nix"> | |||
services.ollama = { | services.ollama = { | ||
enable = true; | enable = true; | ||
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Example: Enable GPU acceleration for Nvidia graphic cards<syntaxhighlight lang="nix"> | Example: Enable GPU acceleration for Nvidia graphic cards | ||
As a standalone package: | |||
<syntaxhighlight lang="nix"> | |||
environment.systemPackages = [ | |||
(pkgs.ollama.override { | |||
acceleration = "cuda"; | |||
}) | |||
]; | |||
</syntaxhighlight> | |||
As a systemd service: | |||
<syntaxhighlight lang="nix"> | |||
services.ollama = { | services.ollama = { | ||
enable = true; | enable = true; | ||
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}; | }; | ||
</syntaxhighlight> | </syntaxhighlight> | ||
To find out whether a model is running on CPU or GPU, you can either | |||
look at the logs of | |||
ollama serve | |||
or while a model is answering run | |||
<syntaxhighlight lang="bash"> | |||
$ ollama ps | |||
NAME ID SIZE PROCESSOR UNTIL | |||
gemma3:4b c0494fe00251 4.7 GB 100% GPU 4 minutes from now | |||
</syntaxhighlight> | |||
In this example we see "100% GPU". | |||
== Usage via CLI == | == Usage via CLI == | ||
=== Download a model and run interactive prompt === | === Download a model and run interactive prompt === | ||
Example: Download and run Mistral LLM model as an interactive prompt<syntaxhighlight lang="bash"> | Example: Download and run Mistral LLM model as an interactive prompt<syntaxhighlight lang="bash"> | ||
ollama run mistral | $ ollama run mistral | ||
</syntaxhighlight>For other models see [https://ollama.ai/library Ollama library]. | </syntaxhighlight>For other models see [https://ollama.ai/library Ollama library]. | ||
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Example: To download and run codellama with 13 billion parameters in the "instruct" variant and send a prompt: | Example: To download and run codellama with 13 billion parameters in the "instruct" variant and send a prompt: | ||
<syntaxhighlight lang="bash"> | <syntaxhighlight lang="bash"> | ||
ollama run codellama:13b-instruct "Write an extended Python program with a typical structure. It should print the numbers 1 to 10 to standard output." | $ ollama run codellama:13b-instruct "Write an extended Python program with a typical structure. It should print the numbers 1 to 10 to standard output." | ||
</syntaxhighlight> | </syntaxhighlight> | ||
Revision as of 21:51, 19 March 2025
Ollama is an open-source framework designed to facilitate the deployment of large language models on local environments. It aims to simplify the complexities involved in running and managing these models, providing a seamless experience for users across different operating systems.
Setup
You can add Ollama in two ways to your system configuration.
As a standalone package:
environment.systemPackages = [ pkgs.ollama ];
As a systemd service:
services.ollama = {
enable = true;
# Optional: load models on startup
loadModels = [ ... ];
};
Configuration of GPU acceleration
Its possible to use following values for acceleration:
- false: disable GPU, only use CPU
- "rocm": supported by most modern AMD GPUs
- "cuda": supported by most modern NVIDIA GPUs
Example: Enable GPU acceleration for Nvidia graphic cards
As a standalone package:
environment.systemPackages = [
(pkgs.ollama.override {
acceleration = "cuda";
})
];
As a systemd service:
services.ollama = {
enable = true;
acceleration = "cuda";
};
To find out whether a model is running on CPU or GPU, you can either look at the logs of ollama serve
or while a model is answering run
$ ollama ps
NAME ID SIZE PROCESSOR UNTIL
gemma3:4b c0494fe00251 4.7 GB 100% GPU 4 minutes from now
In this example we see "100% GPU".
Usage via CLI
Download a model and run interactive prompt
Example: Download and run Mistral LLM model as an interactive prompt
$ ollama run mistral
For other models see Ollama library.
Send a prompt to ollama
Example: To download and run codellama with 13 billion parameters in the "instruct" variant and send a prompt:
$ ollama run codellama:13b-instruct "Write an extended Python program with a typical structure. It should print the numbers 1 to 10 to standard output."
Usage via web API
Other software can use the web API (default at: http://localhost:11434 ) to query ollama. This works well e.g. in Intellij-IDEs with the "ProxyAI" and the "Ollama Commit Summarizer" plugins.
Alternatively, on enabling "open-webui", a web portal is available at: http://localhost:8080/:
services.open-webui.enable = true;
Troubleshooting
AMD GPU with open source driver
In certain cases ollama might not allow your system to use GPU acceleration if it cannot be sure your GPU/driver is compatible.
However you can attempt to force-enable the usage of your GPU by overriding the LLVM target. [1]
You can get the version for your GPU from the logs or like so:
$ nix-shell -p "rocmPackages.rocminfo" --run "rocminfo" | grep "gfx"
Name: gfx1031
In this example the LLVM target is "gfx1031", that is, version "10.3.1", you can then override that value for ollama:
services.ollama = {
enable = true;
acceleration = "rocm";
environmentVariables = {
HCC_AMDGPU_TARGET = "gfx1031"; # used to be necessary, but doesn't seem to anymore
};
rocmOverrideGfx = "10.3.1";
};
If there are still errors, you can attempt to set a similar value that is listed here.