The 4 Essential Dataset Types for LLMs: A Deep Dive

In this informative video, I delve deep into the complexities of different types of dataset formats that can be utilized when fine-tuning LLMs, using Llama 2 as an example. Throughout the video, I discuss four primary dataset types, namely the pre-training format, simple format, instruct format, and chat format, explaining their specific usefulness in model training. I also share insights on the use of datasets for simple format with tags, exploring their potential to make models multi-tasking. The video further explores the instruct format, a good balance between simplicity and flexibility, and the complex nature of the chat format. I conclude with hints at future videos discussing fine-tuning Llama 70B and touching on breakthroughs in big model training on consumer hardware.
Are you a language model enthusiast or a coder keen to understand the best formats for fine-tuning your LLM? If so, be sure to check this out. Remember to subscribe to stay updated with more of my expert content. #LLM #finetuning #MachineLearning #Llama2 #Coding #LearningMachineLearning #AI #python
Discord: / discord
Github: github.com/mallorbc/llama_dat...
Time Stamps:
00:00 - Intro
00:37 - Pretrain Format
01:48 - Simple Format
04:37 - Instruct Format
06:53 - Chat Format
10:30 - Dataset Creation Code
10:54 - Llama 70B Instruct
11:35 - Outro

[@kyledinh8369]

very well explained!

[@Brillibits]

Glad it was helpful!