Dataset: Retrieval-based grounded model generated Q-A pairs #2004

Related to Issue #2004

How it work?

1. Base data: hugging face: wikipedia
2. Cleanse data to shorten the length of the articles
3. Generate Q-A pairs using doc2query
4. Generate Q-A pairs using BART or SearchGPT

Output data

• raw data (BART-based): https://huggingface.co/datasets/michaelthwan/wiki_qa_bart_10000row
• OA format data (BART-based): https://huggingface.co/datasets/michaelthwan/oa_wiki_qa_bart_10000row

Synthetic data based on BART

Synthetic data based on SearchGPT

Code

1. pip install -r requirements.txt (using python 3.10.8)
2. Clean data: 1_clean_wikitext.py
3. Get queries by doc2query 2_wikitext_doc2query.ipynb (I run using colab+local PC)
4. Get responses by BART 3_10k_bart_trial.py or 3_10k_bart_trial.ipynb
5. Convert to OA format 4_convert_to_oa_format.py