Update README.md

README.md

@@ -6,4 +6,31 @@ task_categories:
 tags:
 - chemistry
 - biology
----
+---
+
+# ChEBI-20-MM Dataset
+
+## Overview
+
+The ChEBI-20-MM is an extensive and multi-modal benchmark developed from the ChEBI-20 dataset. It is designed to provide a comprehensive benchmark for evaluating various models' capabilities in the field of molecular science. This benchmark integrates multi-modal data, including InChI, IUPAC, SELFIES, and images, making it a versatile tool for a wide range of molecular tasks.
+
+## Dataset Description
+
+ChEBI-20-MM is an expansion of the original ChEBI-20 dataset, with a focus on incorporating diverse modalities of molecular data. This benchmark is tailored to assess models in several key areas:
+
+- **Molecule Generation**: Evaluating the ability of models to generate accurate molecular structures.
+- **Image and IUPAC Recognition**: Testing models on their proficiency in interpreting and converting molecular images and IUPAC names into other representational formats.
+- **Molecular Captioning**: Assessing the capability of models to generate descriptive captions for molecular structures.
+- **Retrieval Tasks**: Measuring the effectiveness of models in retrieving molecular information accurately and efficiently.
+
+## Utility and Significance
+
+By expanding the data modality variety, this benchmark enables a more comprehensive evaluation of models' performance in multi-modal data handling. It provides an opportunity to explore the intersection of molecular science and advanced computational models.
+
+## How to Use
+
+Model reviews and evaluations related to this dataset can be directly accessed and used via the LLM4Mol link: [LLM4Mol](https://github.com/AI-HPC-Research-Team/LLM4Mol).
+
+## Acknowledgments
+
+The development of the ChEBI-20-MM dataset was inspired by the ChEBI-20 in molecule generation and captioning initiated by MolT5. Additional data information supplements are derived from PubChem.