/large-language-models

Notebooks for Large Language Models (LLMs) Specialization

Primary LanguagePythonOtherNOASSERTION

Large Language Models

This repo contains the notebooks and slides for the Large Language Models: Application through Production course on edX & Databricks Academy.

Notebooks

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.

    repo_1

  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.

    add_repo

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:

    dbc_release1

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

    dbc_release2

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

    dbc_release3

  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:

    dbc_release4
Cluster settings

Which Databricks cluster should I use?

  1. First, select Single Node

    single_node

  2. This courseware has been tested on Databricks Runtime 13.3 LTS for Machine Learning. If you do not have access to a 13.3 LTS 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.

    cluster

    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).

    cpu_settings

    For these notebooks: LLM 04a - Fine-tuning LLMs and LLM04L - Fine-tuning LLMs Lab, you will need the Databricks Runtime 13.3 LTS for Machine Learning with GPU.

    gpu

    Select GPU instance type of g5.2xlarge.

    gpu_settings
Install datasets and models

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.
    install_datasets_file

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

Slides

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.