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Modelfiles | ||
README.md |
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!