Omkar2118/datasets huggingface dataset:
PubChemQA

PubChemQA consists of molecules and their corresponding textual descriptions from PubChem. It contains a single type of question, i.e., please describe the molecule. We remove molecules that cannot be processed by RDKit [Landrum et al., 2021] to generate 2D molecular graphs. We also remove texts with less than 4 words, and crops descriptions with more than 256 words. Finally, we obtain 325, 754 unique molecules and 365, 129 molecule-text pairs. On average, each text description contains 17 words.

Introducing paper: BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine
UniProtQA

UniProtQA consists of proteins and textual queries about their functions and properties. The dataset is constructed from UniProt, and consists 4 types of questions with regard to functions, official names, protein families, and sub-cellular locations. We collect a total of 569, 516 proteins and 1, 891, 506 question-answering samples.

Introducing paper: BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine