llm_tutorial

llm_tutorials

This repository contains the materials used in the LLM Tutorial Workshop, November 29th and 30th 2023.

The workshop agenda is here: link to doc in github.

The workshop material will rely on Jupyter Notebooks which are targeted for running on Google's Colaboratory Platform. The Colab platform gives the user a virtual machine in which to run Python codes including machine learning codes. The VM comes with a preinstalled environment that includes most of what is needed for these tutorials.

Before You Arrive

Do the following before you come to the tutorial:

1. Google Colab Account

• You need a Google Account to use Colaboratory
• Goto Google's Colaboratory Platform and sign in with your google account
• You should see this page
• Click on the New Notebook at the bottom
• Now you will see a new notebook where you can type in python code.
• After you enter code, type <shift>+<enter> to execute the code cell.
• A full introduction to the notebook environment is out of scope for this tutorial, but many can be found with a simple Google search
• We will be using notebooks from this repository during the tutorial, so you should be familiar with how to import them into Colaboratory
• Now you can open the File menu at the top left and select Open Notebook which will open a dialogue box.
• Select the GitHub tab in the dialogue box.
• From here you can enter the url for the github repo: https://github.com/brettin/llm_tutorial and hit <enter>.
• This will show you a list of the Notebooks available in the repo.
• Select the introduction.ipynb file to open and work through it.
• As each session of the tutorial begins, you will simply select the corresponding notebook from this list and it will create a copy for you in your Colaboratory account (all *.ipynb files in the Colaboratory account will be stored in your Google Drive).
• To use a TPU, in the notbook the select Runtime -> Change Runtime Type and you have a dropbox list of hardward settings to choose from where the notebook can run.

2. Sign up for a huggingface account and obtain an access token: https://huggingface.co

• Sign Up (top bar)

Log into huggingface and get an access token:

• Login -> Settings (left pane) -> Access Tokens (left pane) -> New token (center pane)

3. Request access to llama-2 model

• visit this https://huggingface.co/meta-llama/Llama-2-7b-hf and request access to the model
• vist meta website and accept the terms https://ai.meta.com/resources/models-and-libraries/llama-downloads/
• Note: Your Hugging Face account email address MUST match the email you provide on the Meta website, or your request will not be approved.