Use cases
AI compute for training
Model Training GPU Workspaces
Spin up training workspaces for PyTorch experiments, dataset preparation, checkpoints, and repeatable GPU development.
Ready template
Recommended workspace
Template
PyTorch
GPU
H100
Access
Browser + SSH
Billing
Per-hour
porfal create --use-case model-trainingworkspace ready: browser + sshWorkloads
PyTorch training
Experiment runs
Checkpointing
Data preprocessing
Recommended stack
PyTorch
JupyterLab
Ubuntu CUDA
TensorFlow
GPU fit
H100
H200
L40S
Why Porfal
Dedicated GPU compute without infrastructure work.
Pick a GPU, launch the template, connect from browser or SSH, and stop the workspace when the run is done.
Match GPU memory to model size.
Use templates instead of rebuilding environments.
Stop workspaces when training windows end.
Workflow
A short path from GPU to running workload.
1
Select training GPU
2
Choose PyTorch
3
Connect via SSH
4
Run training job