39 lines
1.9 KiB
Markdown
39 lines
1.9 KiB
Markdown
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# Running Ollama on NVIDIA Jetson Devices
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With some minor configuration, Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/). The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack).
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NVIDIA Jetson devices are Linux-based embedded AI computers that are purpose-built for AI applications.
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Jetsons have an integrated GPU that is wired directly to the memory controller of the machine. For this reason, the `nvidia-smi` command is unrecognized, and Ollama proceeds to operate in "CPU only"
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mode. This can be verified by using a monitoring tool like jtop.
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In order to address this, we simply pass the path to the Jetson's pre-installed CUDA libraries into `ollama serve` (while in a tmux session). We then hardcode the num_gpu parameters into a cloned
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version of our target model.
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Prerequisites:
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- curl
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- tmux
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Here are the steps:
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- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.ai/install.sh | sh`
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- Stop the Ollama service: `sudo systemctl stop ollama`
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- Start Ollama serve in a tmux session called ollama_jetson and reference the CUDA libraries path: `tmux has-session -t ollama_jetson 2>/dev/null || tmux new-session -d -s ollama_jetson
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'LD_LIBRARY_PATH=/usr/local/cuda/lib64 ollama serve'`
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- Pull the model you want to use (e.g. mistral): `ollama pull mistral`
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- Create a new Modelfile specifically for enabling GPU support on the Jetson: `touch ModelfileMistralJetson`
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- In the ModelfileMistralJetson file, specify the FROM model and the num_gpu PARAMETER as shown below:
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```
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FROM mistral
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PARAMETER num_gpu 999
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```
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- Create a new model from your Modelfile: `ollama create mistral-jetson -f ./ModelfileMistralJetson`
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- Run the new model: `ollama run mistral-jetson`
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If you run a monitoring tool like jtop you should now see that Ollama is using the Jetson's integrated GPU.
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And that's it!
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