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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
<think>

</think>

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!