Fine-Tuning Quick Start
Train your first fine-tuned model with OpenPipe.
Fine-tuning open and closed models with custom hyperparameters only takes a few clicks.
Before you begin
Before building your first pipeline, make sure you’ve created a dataset and imported at least 10 training entries.
Training a Model
Navigate to Dataset
To train a model, navigate to the dataset you’d like to train your model on. Click the Fine Tune button in the top right corner of the General tab.
Name your Model
Choose a descriptive name for your new model. This name will be used as the model parameter when querying it in code.
You can always rename your model later.
Select Base Model
Select the base model you’d like to fine-tune on. We recommend starting with Llama 3.1 8B if you aren’t sure which to choose.
Adjust Hyperparameters (optional)
Under Advanced Options, you can optionally adjust the hyperparameters to fine-tune your model. You can leave these at their default values if you aren’t sure which to choose.
Start Training
Click Start Training to begin the training process. The training job may take a few minutes or a few hours to complete, depending on the amount of training data, the base model, and the hyperparameters you choose.
To learn more about fine-tuning through the webapp, check out the Fine-Tuning via Webapp page. To learn about fine-tuning via API, see our Fine Tuning via API page.