👋 Welcome to the Support Repository for the DeepLearningAI Event: Building with Instruction-Tuned LLMs: A Step-by-Step Guide
Here are a collection of resources you can use to help fine-tune your LLMs, as well as create a few simple LLM powered applications!
🪡 Fine-tuning Approaches:
![](https://camo.githubusercontent.com/32b2699ad692cf7aeecdfa837b5cf8a05230c49695854b6b26696f4d7c90e6fc/68747470733a2f2f692e696d6775722e636f6d2f695877434161642e706e67)
Instruct-tuning OpenLM's OpenLLaMA on the Dolly-15k Dataset Notebooks:
Notebook |
Purpose |
Link |
Instruct-tuning Leveraging QLoRA |
Supervised fine-tuning! |
Here |
Instruct-tuning Leveraging Lit-LLaMA |
Using Lightning-AI's Lit-LLaMA frame for Supervised fine-tuning |
Here |
Natural Language to SQL fine-tuning using Lit-LLaMA |
Using Lightning-AI's Lit-LLaMA frame for Supervised fine-tuning on the Natural Language to SQL task |
Here |
MarketMail Using BLOOMz Resources:
Notebook |
Purpose |
Link |
BLOOMz-LoRA Unsupervised Fine-tuning Notebook |
Fine-tuning BLOOMz with an unsupervised approach using Sythetic Data! |
Here |
Creating Synthetic Data with GPT-3.5-turbo |
Generate Data for Your Model! |
Here |
🏗️ Converting Models into Applications:
![](https://camo.githubusercontent.com/4d0913e933b31a42f2417a8fb4decb8b54ae2a34de51b75566c1359ade20b15d/68747470733a2f2f692e696d6775722e636f6d2f4e7863485a6b6a2e706e67)
Notebook |
Purpose |
Link |
Open-source LangChain Example |
Leveraging LangChain to build a Hugging Face 🤗 Powered Application |
Here |
Open AI LangChain Example |
Building an Open AI Powered Application |
Here |
🖥️ Demos:
Demo |
Info |
Link |
Instruct-tuned Chatbot Leveraging QLoRA |
This demo is currently powered by the Guanaco Model - will be updated once our instruct-tuned model finishes training! |
Here |
TalkToMyDoc |
Query the first Hitch Hiker's Guide book! |
Here |