A dataset in LLM context, refers to a collection of data used to train or refine a language model like GPT, focusing on understanding and generating human-like text.
There are many datasets available for different tasks and domains that can be used to train or fine-tune LLMs.
Some examples are:
- C4: A large-scale dataset of web text that can be used for pre-training LLMs.
- The Pile: A diverse and high-quality dataset of text from various sources that can be used for pre-training LLMs.
- GLUE (General Language Understanding Evaluation): A benchmark dataset of nine natural language understanding tasks that can be used for evaluating LLMs.
- RedPajama-Data-v2: an Open Dataset with 30 Trillion Tokens for Training Large Language Models.
Training Data is a subset of a dataset that is used to teach the LLM how to perform a specific task, such as natural language understanding or generation.
