# Install Ollama ``` curl -fsSL https://ollama.com/install.sh | sh ``` I prefer to make the model files available for all computers in our working group. Thus I put them on a NAS under /data_1/deepseek. In that case you want to change /etc/systemd/system/ollama.service and add your directory to it: ``` Environment= [PATH BLA BLA] "OLLAMA_MODELS=/data_1/deepseek/models" "HOME=/data_1/deepseek" ``` After that restart systemd with: ``` systemctl restart ollama.service ``` Check the status of the service: ``` systemctl status ollama.service ``` ## Getting the models Now we can get the models: ``` ollama pull deepseek-r1:1.5b ollama pull deepseek-r1:7b ollama pull deepseek-r1:8b ollama pull deepseek-r1:32b ollama pull deepseek-r1:14b ollama pull deepseek-r1:70b ``` However, you want to check first which model you want based on the CPU RAM or the GPU VRAM you have: ``` ollama list | grep deepseek ``` ``` deepseek-r1:1.5b a42b25d8c10a 1.1 GB deepseek-r1:671b 739e1b229ad7 404 GB deepseek-r1:32b 38056bbcbb2d 19 GB deepseek-r1:14b ea35dfe18182 9.0 GB deepseek-r1:7b 0a8c26691023 4.7 GB deepseek-r1:70b 0c1615a8ca32 42 GB deepseek-r1:8b 28f8fd6cdc67 4.9 GB ``` ## Test ``` ollama run deepseek-r1:1.5b ``` ``` >>> Hello Hello! How can I assist you today? 😊 >>> /bye ``` # Using it with VS Code For using Ollama we need a special setting for VS Code. Thus we need to produce instances with different model parameter (or in other words: got to the Modelfile subfolder and check the information their) ``` code_ds32b:latest 995e2d04e071 19 GB code_ds70b:latest 4930f987452d 42 GB code_ds7b:latest 0438bd669fa8 4.7 GB code_ds8b:latest 643346a4074c 4.9 GB code_ds1.5b:latest 2d66604e7b60 1.1 GB code_ds14b:latest 76c930e3d70a 9.0 GB ``` Do not you larger models on your CPU or you will die of old age! ## Install roo code Please make sure that your shell doesn't use something like Starship or the posh packages! Otherwise VS Code can not run terminal command! ![Roo Code](2025-02-02_18-39.png)