Datasets:
Tasks:
Image-to-Text
Formats:
parquet
Sub-tasks:
image-captioning
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Overwrite defaults + add visible note
Browse files
README.md
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license:
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---
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license:
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- cc-by-nc-sa-4.0
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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- split: test
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path: data/test-*
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dataset_info:
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features:
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- name: text
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dtype: string
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- name: image
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dtype: image
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splits:
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- name: train
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num_bytes: 3375690407.25
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num_examples: 90350
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- name: validation
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num_bytes: 185854656.625
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num_examples: 5019
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- name: test
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num_bytes: 184884997.5
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num_examples: 5020
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download_size: 3230633440
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dataset_size: 3746430061.375
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annotations_creators:
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- expert-generated
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language_creators:
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- expert-generated
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language:
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- en
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multilinguality:
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- monolingual
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size_categories:
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- 100K<n<1M
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source_datasets:
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- original
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task_categories:
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- image-to-text
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task_ids:
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- image-captioning
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pretty_name: ChemPile-Caption
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tags:
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- chemistry
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- scientific-captioning
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- scientific-image-to-text
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- libretexts-images
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dataset_version: 1.0.0
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dataset_release_date: '2025-05-18'
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dataset_citation: "@article{mirza2025chempile0,\n title = {ChemPile: A 250GB Diverse
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and Curated Dataset for Chemical Foundation Models},\n author = {Adrian Mirza
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and Nawaf Alampara and Martiño Ríos-García and others},\n year = {2025},\n \
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\ journal = {arXiv preprint arXiv:2505.12534}\n}"
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---
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# ChemPile-Caption
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<div align="center">
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[](https://huggingface.co/datasets/jablonkagroup/chempile-caption)
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[](https://creativecommons.org/licenses/by-nc-sa/4.0/)
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[](https://arxiv.org/abs/2505.12534)
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[](https://chempile.lamalab.org/)
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*A comprehensive collection of image-caption pairs for chemistry-related visual content*
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</div>
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ChemPile-Caption is a dataset designed for image captioning tasks in the field of chemistry. It is part of the ChemPile project, which aims to create a comprehensive collection of chemistry-related data for training language models. This dataset includes a variety of images scraped from LibreTexts related to chemical structures, reactions, and laboratory equipment, along with corresponding captions that describe the content of the images.
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All the content is made open-source under the license cc-by-nc-sa-4.0, allowing for non-commercial use and adaptation with proper attribution.
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The origin of the dataset is the LibreTexts project, which provides a wealth of educational resources in chemistry. The images in this dataset are sourced from various LibreTexts pages, ensuring a diverse range of chemical topics and visual representations. To obtain the images, an in house web scraping process was employed, specifically targeting all the books LibreTexts Chemistry. The images were downloaded and stored in a structured format, with each image associated with its corresponding caption and alt text, filtering out any images that did not have a long enough caption or alt text.
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The dataset is structured into a single simple default configuration, which simplifies the loading and usage of the dataset. The configuration includes the following fields:
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- text: The alt text plus the caption of the image, providing a detailed description of the image content.
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- image: The image, allowing users to access the visual content directly.
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Thus, the resulting ChemPile-Caption dataset contains a total of 100K image-caption pairs.
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## Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("jablonkagroup/chempile-caption")
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print(dataset)
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# DatasetDict({
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# train: Dataset({
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# features: ['text', 'image'],
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# num_rows: 90350
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# })
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# validation: Dataset({
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# features: ['text', 'image'],
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# num_rows: 5019
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# })
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# test: Dataset({
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# features: ['text', 'image'],
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# num_rows: 5020
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# })
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# })
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sample = dataset['train'][0]
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print(f"Sample caption: {sample}")
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# Sample caption: {'text': '2 drawings and a photograph, as described...', 'image': <PIL...}
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```
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## 🏗️ ChemPile Collection
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This dataset is part of the **ChemPile** collection, a comprehensive open dataset containing over 75 billion tokens of curated chemical data for training and evaluating general-purpose models in the chemical sciences.
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### Collection Overview
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- **📊 Scale**: 75+ billion tokens across multiple modalities
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- **🧬 Modalities**: Structured representations (SMILES, SELFIES, IUPAC, InChI), scientific text, executable code, reasoning traces, and molecular images
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- **🎯 Design**: Integrates foundational educational knowledge with specialized scientific literature
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- **🔬 Curation**: Extensive expert curation and validation
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- **📈 Benchmarking**: Standardized train/validation/test splits for robust evaluation
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- **🌐 Availability**: Openly released via Hugging Face
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## 📄 Citation
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If you use this dataset in your research, please cite:
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```bibtex
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@article{mirza2025chempile0,
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title = {ChemPile: A 250GB Diverse and Curated Dataset for Chemical Foundation Models},
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author = {Adrian Mirza and Nawaf Alampara and Martiño Ríos-García and others},
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year = {2025},
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journal = {arXiv preprint arXiv:2505.12534}
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}
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```
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## 👥 Contact & Support
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- **Paper**: [arXiv:2505.12534](https://arxiv.org/abs/2505.12534)
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- **Website**: [ChemPile Project](https://chempile.lamalab.org/)
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- **Dataset**: [Hugging Face](https://huggingface.co/datasets/jablonkagroup/chempile-caption)
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- **Issues**: Please report data issues or questions via the Hugging Face dataset page
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---
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<div align="center">
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<i>Part of the ChemPile project - Advancing AI for Chemical Sciences</i>
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</div>
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