No-code SFT, DPO, or AutoML sweep - anyone on your team can launch and monitor training jobs for LLMs and vision models.
Any team member can launch SFT, DPO, or AutoML training jobs for LLMs (1B–20B+ params) and vision models from a point-and-click dashboard. No training scripts, no GPU cluster management, no ML engineer required.
Choose between LLM fine-tuning (SFT for task adaptation, DPO for preference alignment) or computer vision training. Select your base model from the supported library - 1B through 20B+ parameters - and point the platform at your annotated dataset. No YAML, no scripts, no infrastructure decisions required.
QpiAI PRO's AutoML engine evaluates the training objective, dataset size, and model architecture to select optimal learning rate, batch size, warmup schedule, and regularization parameters. The GPU cluster is provisioned and scaled automatically - you never touch cloud quotas or instance types.
A real-time dashboard streams training loss, validation accuracy, GPU utilisation, and estimated time to completion. If a run is diverging, you can intervene immediately. When training completes, models are automatically packaged for one-click export and deployment - no post-processing required.
Supervised fine-tuning and direct preference optimisation for LLMs - both available through a point-and-click interface. Adapt any supported model to your domain without writing training code.
Automated search across learning rate, batch size, dropout, and architecture choices. AutoML finds configurations that would take a senior ML engineer days to tune manually - in a single automated sweep.
The platform provisions the right GPU cluster size for your model and dataset - and scales up dynamically if throughput falls below target. You pay for what you use, not what you reserved.
Live dashboards stream loss curves, accuracy, GPU utilisation, and estimated time to completion. Catch diverging runs immediately - before you waste hours of compute time.
From compact 1B models optimised for edge inference to 20B+ flagship LLMs for maximum capability - all supported with the same no-code training workflow and infrastructure management.
Trained models are automatically packaged in standard formats. Export to HuggingFace, ONNX, or TensorRT - or deploy directly to QpiAI PRO's inference endpoints with a single click.
Start a training run today. No credit card, no ML engineers, no infrastructure overhead required.