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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**.
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