Skip to content

Latest commit

 

History

History
71 lines (52 loc) · 2 KB

docker.md

File metadata and controls

71 lines (52 loc) · 2 KB

Ollama Docker image

CPU only

docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

Nvidia GPU

Install the NVIDIA Container Toolkit.

Install with Apt

  1. Configure the repository
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
    | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
  1. Install the NVIDIA Container Toolkit packages
sudo apt-get install -y nvidia-container-toolkit

Install with Yum or Dnf

  1. Configure the repository
curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo \
    | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
  1. Install the NVIDIA Container Toolkit packages
sudo yum install -y nvidia-container-toolkit

Configure Docker to use Nvidia driver

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

Start the container

docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

AMD GPU

To run Ollama using Docker with AMD GPUs, use the rocm tag and the following command:

docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm

Run model locally

Now you can run a model:

docker exec -it ollama ollama run llama3

Try different models

More models can be found on the Ollama library.