datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SWE-bench-Science
SWE-bench Science
SWE-bench Science evaluates coding agents on software-engineering tasks drawn from scientific-computing repositories. The release contains 119 tasks across 20 scientific domains, with isolated environments and separate programmatic verifiers.
GitHub release repository: OpenMOSS/SWE-bench-Science
Runtime images: Docker Hub, pinned by immutable linux/amd64 digests
Evaluation framework: Pier, compatible with Harbor task format
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/SWE-bench-Science.Aneumo
Aneumo Datasets
AneumoDataset is a comprehensive multi-modal dataset containing 3D anatomical structures and simulated hemodynamic parameters for cerebral aneurysms, supporting both computational modeling and AI-based analysis.
ScienceQAThis is the ScientificQA dataset by Saikh et al (2022).
@article{10.1007/s00799-022-00329-y,
author = {Saikh, Tanik and Ghosal, Tirthankar and Mittal, Amish and Ekbal, Asif and Bhattacharyya, Pushpak},
title = {ScienceQA: A Novel Resource for Question Answering on Scholarly Articles},
year = {2022},
journal = {Int. J. Digit. Libr.},
month = {sep}
}
generalization-science-datascience_materialstest-sciencediffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04 Contains maximum activating examples for all the features of our crosscoder trained on gemma 2 2B layer 13 available here: https://huggingface.co/Butanium/gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04/blob/main/README.md
base_examples.pt contains all the maximum examples of the feature on a subset of validation test of fineweb
chat_examples.pt is the same but for lmsys chat data
chat_base_examples.pt is a merge of the two above files.
All files are of the type dict[int, list[tuple[float… See the full description on the dataset page: https://huggingface.co/datasets/science-of-finetuning/diffing-stats-gemma-2-2b-crosscoder-l13-mu4.1e-02-lr1e-04.science_biologymodis-lake-powell-toy-dataset
MODIS Water Lake Powell Toy Dataset
Dataset Summary
Tabular dataset comprised of MODIS surface reflectance bands along with calculated indices and a label (water/not-water)
Dataset Structure
Data Fields
water: Label, water or not-water (binary)
sur_refl_b01_1: MODIS surface reflection band 1 (-100, 16000)
sur_refl_b02_1: MODIS surface reflection band 2 (-100, 16000)
sur_refl_b03_1: MODIS surface reflection band 3 (-100, 16000)
sur_refl_b04_1: MODIS… See the full description on the dataset page: https://huggingface.co/datasets/nasa-cisto-data-science-group/modis-lake-powell-toy-dataset.science_physicsKaggle-LLM-Science-Exam
Dataset Card for [LLM Science Exam Kaggle Competition]
Dataset Summary
https://www.kaggle.com/competitions/kaggle-llm-science-exam/data
Languages
[en, de, tl, it, es, fr, pt, id, pl, ro, so, ca, da, sw, hu, no, nl, et, af, hr, lv, sl]
Dataset Structure
Columns
prompt - the text of the question being asked
A - option A; if this option is correct, then answer will be A
B - option B; if this option is correct, then answer will be B
C - option C; if this… See the full description on the dataset page: https://huggingface.co/datasets/Sangeetha/Kaggle-LLM-Science-Exam.tabrepair-science-repair-under-shift
TabRepair Science: Repair Under Shift
TabRepair Science is a finite authored benchmark for a deceptively hard
question: does better tabular cell repair produce better downstream models
under distribution shift?
The 3,648-row pilot spans three structural generator families, missingness and
present-value contamination, four test regimes, eight repair representations,
and five downstream learners. A separate eight-world sensitivity layer tests a
damage-aware v2 candidate without… See the full description on the dataset page: https://huggingface.co/datasets/haidang2405/tabrepair-science-repair-under-shift.nasa-science-repos-sme-benchmark
NASA Science Repos SME Benchmark
A benchmark dataset for evaluating retrieval systems on NASA science repository discovery tasks. This dataset contains expert queries, a corpus of NASA science GitHub repositories, and relevance judgments.
Dataset Structure
Files
├── corpus.jsonl # 5,264 repositories with full metadata
├── queries.jsonl # 219 expert queries
└── qrels/
├── earth.tsv # Earth Science relevance judgments (162)
├──… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-repos-sme-benchmark.web-of-science-with-label-texts
Dataset Description:
The data is partitioned according to a 75/15/15 train/test/validate split.
Each entry has an abstract (which is the input text for classification), a domain (a label from the list below), and an area (a subdomain of the paper, such as CS -> computer graphics, which takes on one of 134 possible values).
All the attributes are strings.
Domain labels:
- Computer Science
- Electrical Engineering
- Psychology
- Mechanical Engineering,
- Civil Engineering
- Medical… See the full description on the dataset page: https://huggingface.co/datasets/river-martin/web-of-science-with-label-texts.Science-Discoverydata-science-job-salaries
Dataset Card for Data Science Job Salaries
Dataset Summary
Content
Column
Description
work_year
The year the salary was paid.
experience_level
The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director
employment_type
The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance
job_title… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.nasa-science-code-benchmark-v0.1.1
NASA Code Retrieval Benchmark v0.1.1
This repository is an updated version of the NASA Code Retrieval Benchmark. It provides a code retrieval benchmark based on code from 7 programming languages sourced from NASA's GitHub repositories.
What's New in v0.1.1?
v0.1.1 introduces a hierarchical structure and official Hugging Face dataset configurations. This allows you to evaluate models specifically by language or by query category without data redundancy in the file system.… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-code-benchmark-v0.1.1.science_qa_txt_only_standardizedcomputer-science-synthetic-datasetDense-Information-Science-Physics-Dataset
Dense Information With Multiple Fine-tuned Variations
This dataaset has multiple for each input to learn how to express the same answer in different ways
Dataset Structure
The dataset contains two columns:
Column
Description
input
A science or quantum-physics question
output
A conversational answer to the question
Example:
{
"input": "What is quantum entanglement?",
"output": "Quantum entanglement is when two quantum systems share one… See the full description on the dataset page: https://huggingface.co/datasets/StarpowerTechnology/Dense-Information-Science-Physics-Dataset.jain-developability-cleanScienceQA
xbench-evals
🌐 Website | 📄 Paper | 🤗 Dataset
Evergreen, contamination-free, real-world, domain-specific AI evaluation framework
xbench is more than just a scoreboard — it's a new evaluation framework with two complementary tracks, designed to measure both the intelligence frontier and real-world utility of AI systems:
AGI Tracking: Measures core model capabilities like reasoning, tool-use, and memory
Profession Aligned: A new class of evals grounded in workflows, environments… See the full description on the dataset page: https://huggingface.co/datasets/xbench/ScienceQA.nasa-science-github-repos
NASA Science GitHub Repositories
A curated index of 5,264 GitHub repositories relevant to the NASA Science Mission
Directorate (SMD), spanning five science divisions: Earth Science, Astrophysics,
Planetary Science, Heliophysics, and Biological & Physical Sciences.
This dataset is designed to support research on information retrieval and
discoverability of open-source scientific software.
Licensing and Intellectual Property
This dataset is released under CC-BY-4.0 and… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-github-repos.science-journal-for-kids-data
Science Journal for Kids Data
This repository contains a dataset of abstracts from the Science Journal for Kids website and the original academic papers. It includes metadata such as titles, URLs, reading levels, and links to the full academic papers. The dataset is designed to support research and analysis of educational content tailored for young learners.
Data
The dataset is a curated collection of 284 original scientific abstracts and their adapted abstracts for… See the full description on the dataset page: https://huggingface.co/datasets/loukritia/science-journal-for-kids-data.nasa-science-code-benchmark-v0.1
NASA Code Retrieval Benchmark v0.1
Note: This dataset has been superseded by nasa-impact/nasa-science-code-benchmark-v0.1.1, which introduces a hierarchical structure, official Hugging Face dataset configurations, and evaluation by NASA science division. Please use v0.1.1 for new work.
This dataset provides a code retrieval benchmark based on code from 7 programming languages (Python, C, C++, Java, JavaScript, Fortran, and Matlab) sourced from NASA's GitHub repositories. It serves… See the full description on the dataset page: https://huggingface.co/datasets/nasa-impact/nasa-science-code-benchmark-v0.1.diffing-stats-SAE-difference_cb-gemma-2-2b-L13-k100-x8-lr1e-04-local-shufflingScienceAgentBench
ScienceAgentBench
The advancements of language language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about their true capabilities.
In this work, we call for rigorous assessment of agents on individual tasks in a scientific workflow before making bold claims on end-to-end automation.
To this end, we present ScienceAgentBench, a new benchmark for… See the full description on the dataset page: https://huggingface.co/datasets/BDDSSD/ScienceAgentBench.awesome-food-allergy-datasets
Awesome Food Allergy Datasets
A curated collection of datasets, databases, and computational resources for food allergy research, allergen identification, drug development, and clinical applications.
🧬 Dataset Description
Dataset Summary
Food allergy affects over 220 million people worldwide. This repository serves as the first comprehensive, open collection of AI-ready datasets for food allergy research—spanning clinical trials, immunotherapy, genomics… See the full description on the dataset page: https://huggingface.co/datasets/hugging-science/awesome-food-allergy-datasets.Nemotron-RL-Science-v1-prompt-only
Nemotron-RL-Science-v1-prompt-only
Prompt-only extraction from nvidia/Nemotron-RL-Science-v1.
Files:
prompts.csv: one prompt extraction record per source row. Records include
prompt, separated system_prompt, and structured tools when the source row
defines available tools. Nested values are JSON-encoded inside CSV cells.
summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.
null_or_empty_rows.md: row indexes where prompt extraction… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Science-v1-prompt-only.Science_Articles