
ANZ_LLM_Bootcamp
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This repository is dedicated to the ANZ LLM Workshop Series, providing a series of notebooks developed and tested on Databricks ML Runtime 14.3. The notebooks cover topics such as setting up HuggingFace models, working with sample documents, constructing RAG architectures, and running applications on the driver node in Databricks. Additionally, the repository offers recordings of past webinars and further reading materials related to LLM.
README:
This repo is for the ANZ LLM Workshop Series.
This series of notebooks have been developed and tested on Databricks ML Runtime 14.3
They are designed to be run alongside Databricks Provisioned Throughput Foundation Model APIs See: Databricks AWS Docu
You can deploy a model endpoint with a chat model like DBRX / Mistral / Llama 2. See: Creating Model Endpoints
0.1_lab_setup(instructor_only)
Notebook is to be run by instructor. This downloads HuggingFace models and some sample documents for us to work with. The workspace will need to have access to *.huggingface.co
for the models and wikipedia and some other websites for pdf data.
0.x_
series notebooks go through LLM basics and setup a basic RAG app powered by HuggingFace open source models.
1.x_
series notebooks cover go into more detail about constructing and tuning RAG Architectures.
It is possible to run applications on the driver node in Databricks. The app
folder contains examples of how to do this.
The 2023 version of these materials were presented in a webinar see: LLM Basics 0.x_ materials LLM Advanced 1.x_ materials
- We have a great catalog of LLM related talks at the Data and AI Summit link here
- For a set of great examples on fine-tuning these LLMs, we recommend looking at the Databricks ML examples repo
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