Vector Lab - Model Training with Databricks API - Step-by-Step Tutorial (With DEMO!)

In this video, we show how to perform model training using the Databricks API (including a demo!).

We download a demo from dbdemos.ai and use it to fine-tune a model. We show how to fine-tune a chatbot on the Databricks documentation using the Databricks Model Training API. This process involves ensuring your data is in the correct format, using a Retrieval-Augmented Generation (RAG) layer, and logging the model in Unity Catalog.

Key steps we cover include:
- Downloading and preparing demo notebooks.
- Formatting data for the chat completion model.
- Fine-tuning the model using the MosaicML Model Training API.
- Monitoring training metrics with MLflow.
- Running fine-tuning jobs via the API and UI.

Join us to see how you can efficiently train and fine-tune models with Databricks, ensuring high-quality results with properly preprocessed data.

Check out Databricks tutorials available to everyone at dbdemos.ai. These tutorials cover various segments such as the whole platform, data engineering, and data science. https://www.databricks.com/resources/...

Want to know why you should fine-tune a model? Check this video: Vector Lab - Databricks Mosaic AI Mod...