Torch / PyTorch¶

Check if Torch can find your GPU
```
import torch; torch.cuda.is_available()
```
- It should return True; otherwise, Torch cannot find your GPU.

Anaconda / Conda¶

Create a new conda environment
```
conda create -n env_name
```
Create a new conda environment with a specific Python version and libraries
```
conda create -n env_name python=3.11 pandas matplotlib
```
Deactivate a conda environment
```
conda deactivate
```
Remove a conda environment
```
conda remove -n env_name --all
```

Docker Commands¶

List all Docker containers (including stopped ones)
```
docker ps -a
```
List all Docker images
```
docker images
```
See hardware usage of running Docker images
```
docker stats
```
Remove a Docker container
```
docker rm -f <container_id>
```

Enter the shell of a running Docker container

sudo docker exec -it <container_id> /bin/bash

Run Open-WebUI using Docker to make it accessible across the network

sudo docker run -d --network=host -v open-webui:/app/backend/data \
-e OLLAMA_BASE_URL=http://127.0.0.1:11434 \
--name open-webui-main --restart always \
ghcr.io/open-webui/open-webui:cuda

SCP (Secure Copy)¶

Send a file from your local computer to a remote machine
```
scp [options/flags] path/to/local/file remote_user@remote_ip:/path/to/destination
```
- Find your remote_user using the whoami command.
- Find your remote machine’s IP address using hostname -I.
Example:
```
scp -r ./models appuser@192.168.1.229:/usr/share/ollama/.ollama/models
```

Rsync and Parallel for Fast File Transfers¶

(Stay tuned! It’s coming soon)