RAGBench

Dataset Overview

RAGBEnch is a large-scale RAG benchmark dataset of 100k RAG examples. It covers five unique industry-specific domains and various RAG task types. RAGBench examples are sourced from industry corpora such as user manuals, making it particularly relevant for industry applications.

RAGBench comrises 12 sub-component datasets, each one split into train/validation/test splits

Usage

from datasets import load_dataset

# load train/validation/test splits of individual subset
ragbench_hotpotqa = load_dataset("rungalileo/ragbench", "hotpotqa")

# load a specific split of a subset dataset
ragbench_hotpotqa = load_dataset("rungalileo/ragbench", "hotpotqa", split="test")

# load the full ragbench dataset
ragbench = {}
for dataset in ['covidqa', 'cuad', 'delucionqa', 'emanual', 'expertqa', 'finqa', 'hagrid', 'hotpotqa', 'msmarco', 'pubmedqa', 'tatqa', 'techqa']:
  ragbench[dataset] = load_dataset("rungalileo/ragbench", dataset)