Make RAG evaluation dataset. 100% compatible to AutoRAG
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
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AutoRAG Data Creation is a tool designed to create, chunk, and generate QA datasets from PDF files. It is 100% compatible with AutoRAG, making it an ideal solution for constructing high-quality RAG (Retrieval-Augmented Generation) evaluation datasets. This tool simplifies the process of converting complex documents into structured question-answer pairs, enabling efficient data preparation for AI model training and evaluation.
1. Can AutoRAG Data Creation handle multiple PDF files at once?
Yes, AutoRAG Data Creation supports batch processing, allowing you to process multiple PDF files simultaneously to save time.
2. How do I customize the dataset creation process?
You can customize the dataset by setting specific parameters such as chunk size, question types, and formatting requirements during the initial setup.
3. Is AutoRAG Data Creation compatible with other tools besides AutoRAG?
While it is specifically optimized for AutoRAG, the generated datasets are structured in a standard format, making them compatible with other RAG systems with minimal adjustments.