Use cases
AI compute for fine-tuning
Fine-tuning GPU Workspaces
Provision workspaces for adapter training, supervised fine-tuning, evaluation, and model packaging.
Ready template
Recommended workspace
Template
PyTorch
GPU
H100
Access
Browser + SSH
Billing
Per-hour
porfal create --use-case fine-tuningworkspace ready: browser + sshWorkloads
LoRA
QLoRA
SFT runs
Evaluation jobs
Recommended stack
PyTorch
JupyterLab
Ubuntu CUDA
vLLM
GPU fit
H100
H200
RTX 6000 Ada
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.
Use high-VRAM GPUs only when fine-tuning runs need them.
Keep training artifacts isolated per workspace.
Move from fine-tuning to inference testing quickly.
Workflow
A short path from GPU to running workload.
1
Choose high VRAM
2
Prepare dataset
3
Run fine-tune
4
Evaluate model