llama llama red pajama

Llama_with_llama3_1

# a machine with a GPU would be nice. makes it faster.

# install Ollama - a runner for the models

sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
sudo chmod +x /usr/bin/ollama
sudo useradd -r -s /bin/false -m -d /usr/share/ollama ollama

# create service unit file
tee /usr/lib/systemd/system/ollama.service > /dev/null <<EOF
[Unit]
Description=Ollama Service
After=network-online.target

[Service]
ExecStart=/usr/bin/ollama serve
User=ollama
Group=ollama
Restart=always
RestartSec=3
Environment="OLLAMA_HOST=0.0.0.0" 
Environment="OLLAMA_ORIGINS=*"

[Install]
WantedBy=default.target
EOF

# reload the systemd daemon and enable ollama

sudo systemctl daemon-reload
sudo systemctl enable ollama
sudo systemctl start ollama


# testing
sudo lsof -i :11434
sudo systemctl stop ollama
export OLLAMA_HOST=0.0.0.0 
ollama serve




# run the llama3.1 model

ollama run llama3.1

# restart the ollama runner 
sudo service ollama restart


# watch the logs 
journalctl -xeu ollama

# watch nvidia GPU

watch -n 1 nvidia-smi

# DeepSeek Coder is trained from scratch on both 87% code and 13% natural language in English and Chinese. Each of the models are pre-trained on 2 trillion tokens.

### Models available

ollama run deepseek-coder
ollama run deepseek-coder:6.7b
ollama run deepseek-coder:33b

### API access to your own machine

Example using curl:

curl -X POST http://your-machine-ip-address:11434/api/generate -d '{
  "model": "llama3.1",
  "prompt":"Why is the sky blue?"
 }'
 
 
# Enchanted App on iOS app store

http://your-machine-ip-address:11434



# zed editor integrates personal ollama
# vscode editor integration with personal ollama
# obsidian notes integration via khoj plugin connected to personal ollama

https://openwebui.com/#open-webui-community