Local AI training
Train models on your hardware with SOUP
Quietly’s Train tab integrates SOUP so you can teach a model in your own words, on your own machine. Compose SFT runs from a local HF folder and JSONL dataset—Soup ready on everyday GPUs, including Intel.
SOUP inside Quietly
Open Train → Compose, pick method (e.g. A · SFT), base model, and dataset, then press Train—Soup ready status when the stack is healthy.
Low-spec friendly
Built for everyday machines—status badges surface GPU, Doctor OK, and Local only so you know training stays on-device.
Nothing leaves your computer
Your fine-tune data never enters a vendor training pipeline. Keep proprietary corpora on the workstation.
Who trains locally with Quietly?
Builders adapting small models to a house style, domain jargon, or private docs—without uploading datasets to hosted fine-tune services.
Teams evaluating on-device training for compliance: Quietly keeps the workflow inside the same privacy-first desktop app as Chat, IDE, and Image.
Getting started with the Train tab
Install Quietly, open Train, select a base model and a local dataset path, then start a SOUP run. Monitor epochs and loss on-device.
After training, use the adapted model in Quietly Chat or the offline AI IDE—still fully local after setup.