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Fine-tune an LLM

In this tutorial, you'll build a pipeline with Dagster that:

  • Loads a public Goodreads JSON dataset into DuckDB
  • Performs feature engineering to enhance the data
  • Creates and validates the data files needed for an OpenAI fine-tuning job
  • Generate a custom model and validate it
Prerequisites

To follow the steps in this guide, you'll need:

  • Basic Python knowledge
  • Python 3.9+ installed on your system. Refer to the Installation guide for information.
  • Familiarity with SQL and Python data manipulation libraries, such as Pandas.
  • Understanding of data pipelines and the extract, transform, and load process (ETL).

Step 1: Set up your Dagster environment​

First, set up a new Dagster project.

  1. Clone the Dagster repo and navigate to the project:

    cd examples/dagster-llm-fine-tune

  2. Create and activate a virtual environment:

    uv venv dagster_tutorial
    source dagster_tutorial/bin/activate

  3. Install Dagster and the required dependencies:

    uv pip install -e ".[dev]"

Step 2: Launch the Dagster webserver​

To make sure Dagster and its dependencies were installed correctly, navigate to the project root directory and start the Dagster webserver:

followed by a bash code snippet for

dagster dev

Next steps​