Add dataset card with citations and ORDerly descriptions

README.md

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+
+---
+license: cc-by-4.0
+task_categories:
+- text-generation
+- feature-extraction
+language:
+- en
+tags:
+- chemistry
+- chemoinformatics
+- reaction-prediction
+- RAG
+pretty_name: ORDerly Styrene Mizoroki-Heck RAG Dataset
+size_categories:
+- 10K<n<100K
+---
+
+# ORDerly: Styrene Mizoroki-Heck RAG-Ready Dataset
+
+This repository contains chemical reaction data formatted for **Retrieval-Augmented Generation (RAG)** systems. 
+The data is a processed version of the **ORDerly** benchmark, specifically focusing on reaction conditions and forward/retro prediction tasks.
+
+## Dataset Structure
+The data is split into 10,000-row Parquet chunks to prevent Out-of-Memory (OOM) errors during ingestion into vector databases. 
+It includes:
+- **orderly_condition**: Solvents and agents given reactants and products.
+- **orderly_forward**: Product prediction given reactants and agents.
+- **orderly_retro**: Retrosynthesis planning.
+
+## How to Use
+```python
+from datasets import load_dataset
+dataset = load_dataset("Azzindani/Open_Reaction_Data", streaming=True)
+
+```
+
+## Citations and Data Source
+
+This dataset is based on the **ORDerly** framework. If you use this data, please cite the original authors:
+
+**Paper:**
+
+> Wigh, D. S., et al. (2024). ORDerly: Data Sets and Benchmarks for Chemical Reaction Data. *Journal of Chemical Information and Modeling*. [https://doi.org/10.1021/acs.jcim.4c00292](https://pubs.acs.org/doi/10.1021/acs.jcim.4c00292)
+
+**Original Dataset:**
+
+> Wigh, D. S., et al. (2023). ORDerly chemical reactions condition benchmarks. *Figshare*. [https://doi.org/10.6084/m9.figshare.23298467.v4](https://figshare.com/articles/dataset/ORDerly_chemical_reactions_condition_benchmarks/23298467/4)
+
+## License
+
+Licensed under **CC BY 4.0**.