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Azzindani/Open_Reaction_Data

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:… See the full description on the dataset page: https://huggingface.co/datasets/Azzindani/Open_Reaction_Data.

sourceHugging Facecc-by-4.0updated 7mo agoView on Hugging Face
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Dataset Card

license: cc-by-4.0 task_categories:

  • —text-generation
  • —feature-extraction language:
  • —en tags:
  • —chemistry
  • —chemoinformatics
  • —reaction-prediction
  • —RAG prettyname: ORDerly Styrene Mizoroki-Heck RAG Dataset sizecategories:
  • —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

Original Dataset:

Wigh, D. S., et al. (2023). ORDerly chemical reactions condition benchmarks. Figshare. https://doi.org/10.6084/m9.figshare.23298467.v4

License

Licensed under CC BY 4.0.