databricks-academy/large-language-models

How to Import the Repo into Databricks?

1. You first need to add Git credentials to Databricks. Refer to documentation here.

2. Click Repos in the sidebar. Click Add Repo on the top right.

   

3. Clone the "HTTPS" URL from GitHub, or copy https://github.com/databricks-academy/large-language-models.git and paste into the box Git repository URL. The rest of the fields, i.e. Git provider and Repository name, will be automatically populated. Click Create Repo on the bottom right.

   

How to Import the files from .dbc releases on GitHub

1. You can download the notebooks from a release by navigating to the releases section on the GitHub page:

   

2. From the releases page, download the .dbc file. This contains all of the course notebooks, with the structure and meta data.

   

3. In your Databricks workspace, navigate to the Workspace menu, click on Home and select Import:

   

4. Using the import tool, navigate to the location on your computer where the .dbc file was dowloaded from Step 1. Once you select the file, click Import, and the files will be loaded and extracted to your workspace:

   

Which Databricks cluster should I use?

1. First, select Single Node

   

2. This courseware has been tested on Databricks Runtime 13.1 for Machine Learning. If you do not have access to a 13.1 ML Runtime cluster, you will need to install many additional libraries (as the ML Runtime pre-installs many commonly used machine learning packages), and this courseware is not guaranteed to run.

   

   For all of the notebooks except LLM 04a - Fine-tuning LLMs and LLM04L - Fine-tuning LLMs Lab, you can run them on a CPU just fine. We recommend either i3.xlarge or i3.2xlarge (i3.2xlarge will have slightly faster performance).

   

   For these notebooks: LLM 04a - Fine-tuning LLMs and LLM04L - Fine-tuning LLMs Lab, you will need the Databricks Runtime 13.1 for Machine Learning with GPU.

   

   Select GPU instance type of g5.2xlarge.

   

How do I install the datasets and models locally?

1. To improve performance of the code, we highly recommend pre-installing the datasets and models by running the LLM 00a - Install Datasets notebook.
   

2. You should run this script before running any of the other notebooks. This can take up to 25mins to complete.

Where do I download course slides?

Please click the latest version under the Releases section. You will be able to download the slides in PDF.