datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MaterialsSaddles
MaterialsSaddles
A high-throughput library of converged transition states for solid-state and
surface chemistry.
Hub URL: https://huggingface.co/datasets/SciLM/MaterialsSaddles
Released by SciLM.ai: https://www.scilm.ai
34,135,597 fully converged transition states computed by massively-parallel
saddle searches on top of public materials and catalysis datasets, using the
SaddleMill package and Meta's
uma-s-1p2 machine-learning
interatomic potential.
Each entry in a file is a… See the full description on the dataset page: https://huggingface.co/datasets/SciLM/MaterialsSaddles.Japanese-Materials
仓库信息
电报地址：https://t.me/vomebook ，有问题请在：https://huggingface.co/datasets/VoiceOfML/Japanese-Materials/discussions 提出。
此仓库存储日共资料：https://huggingface.co/datasets/VoiceOfML/Japanese-Materials/tree/main 。
请使用：https://voiceofml-search.hf.space/Japanese-Materials 进行文件检索（备用搜索站：https://vomebook.github.io/search/#/Japanese-Materials ）。
可使用：https://voiceofml-search.hf.space/Japanese-Materials?wide=1 进行仓库内容查看（备用站：https://voiceofml-search.hf.space/Japanese-Materials?wide=1 ）。… See the full description on the dataset page: https://huggingface.co/datasets/VoiceOfML/Japanese-Materials.sama_material_centric_video_dataset
Dataset Card for sama_material_aware
This is the training and evaluation dataset introduced alongside SAMa: Material-Aware 3D Selection and Segmentation. It is an object-centric synthetic video dataset with dense per-frame, per-material pixel-level segmentation annotations, designed to fine-tune video object-selection models for the task of material selection.
This FiftyOne dataset contains 500 samples (450 train, 50 test).
Installation
pip install -U fiftyone… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/sama_material_centric_video_dataset.sec-material-contracts
Material Contracts (Exhibit 10) from SEC/EDGAR
Because sometimes you need 1,141,632 examples of corporate legalese to train your next model ☕
Dataset Summary
Picture this: 1,141,632 material contracts (Exhibit 10) painstakingly collected from sec.gov's EDGAR database. We're talking about legal agreements spanning from 1994 to 2025 Q1, sourced from 10-K, 10-Q, and 8-K filings. Think of Exhibit 10 as the treasure trove where companies hide their most important legal… See the full description on the dataset page: https://huggingface.co/datasets/chenghao/sec-material-contracts.sih26099-cpse-material-codes
SIH 26099 — Collected Dataset
AI-Driven Standardization & Harmonization of Material Codes Across CPSEs
This workspace holds the data-collection stage only — no model, no training,
no feature engineering. Just raw public sources, their extracted structured
form, and the reference taxonomies/vocabularies the harmonisation step needs.
Collected live on 2026-09-08. All row counts below were verified by reading
the files back with pandas.
1. Headline numbers… See the full description on the dataset page: https://huggingface.co/datasets/sarthak20024/sih26099-cpse-material-codes.course-materialMPM-Verse-MaterialSim-Small
Dataset Card for MPMVerse Physics Simulation Dataset
Dataset Summary
This dataset contains Material-Point-Method (MPM) simulations for various materials, including water, sand, plasticine, elasticity, jelly, rigid collisions, and melting. Each material is represented as point-clouds that evolve over time. The dataset is designed for learning and predicting MPM-based physical simulations.
Supported Tasks and Leaderboards
The dataset supports tasks such as:… See the full description on the dataset page: https://huggingface.co/datasets/hrishivish23/MPM-Verse-MaterialSim-Small.matcalc-bench
wbm-random-pbe52-equilibrium-2025.1.json.gz
Relaxed structure, un-/corrected energy and un-/corrected formation energy per atom of random sampled structures in WBM downloaded in Jan 2025.
Excludes deprecated structures, see Materials Project Documentation and pymatgen#2968 for details.
Corrects energy using MaterialsProject2020Compatibility.
Uses PBE PAW datasets version 52.
972 materials.
mp-binary-pbe-elasticity-2025.1.json.gz
Elastic moduli of binaries in Materials… See the full description on the dataset page: https://huggingface.co/datasets/materialyze/matcalc-bench.matpes
Dataset Summary
Potential energy surface datasets with near-complete coverage of the periodic table are used to train foundation
potentials (FPs), i.e., machine learning interatomic potentials (MLIPs) with near-complete coverage of the periodic
table. MatPES is an initiative by the Materialyze Lab and the Materials Project to address
critical deficiencies in such PES datasets for materials.
Accuracy. MatPES is computed using static DFT calculations with stringent converegence… See the full description on the dataset page: https://huggingface.co/datasets/materialyze/matpes.sec-material-contracts-qa800+ EDGAR contracts with PDF images and key information extracted by the OpenAI GPT-4o model.
The key information is defined as follows:
class KeyInformation(BaseModel):
agreement_date : str = Field(description="Agreement signing date of the contract. (date)")
effective_date : str = Field(description="Effective date of the contract. (date)")
expiration_date : str = Field(description="Service end date or expiration date of the contract. (date)")
party_address : str =… See the full description on the dataset page: https://huggingface.co/datasets/chenghao/sec-material-contracts-qa.material_fracturingpersonal_study_material_09deep-swe-1-1-materialized
DeepSWE 1.1 — materialized
A tabular materialization of DeepSWE
v1.1 — Datacurve's 113-task benchmark for coding agents — repackaged from
datacurve-ai/deep-swe into one
parquet row per task. This is a third-party repack for tooling convenience,
not an official Datacurve release.
Source commit: see manifest.json (source_commit) — every file is
carried over unmodified into columns.
Integrity: manifest.json records the parquet's sha256 and a per-task
content hash (sha256 over each… See the full description on the dataset page: https://huggingface.co/datasets/luolc/deep-swe-1-1-materialized.AgiBotWorld-Beta_G1_task_566_Place_the_goods_in_the_material_box_on_the_shelf
agibot_task_566
This dataset converts the AgiBot format uniformly into LeRobot V3.0.
Dataset Statistics
robot_name: G1
end_effector: 夹爪
task: 将物料箱中的货物放到货架上part_1
total_episodes: 281
total_tasks: 1
size: 31G
Dataset Structure
├── data
│ └── chunk-xxx
│ ├── file-xxx.parquet
├── meta
│ ├── episodes
│ │ └── chunk-xxx
│ │ └── file-xxx.parquet
│ ├── info.json
│ ├── stats.json
│ └── tasks.parquet
└── videos
├──… See the full description on the dataset page: https://huggingface.co/datasets/BAAI-DataCube/AgiBotWorld-Beta_G1_task_566_Place_the_goods_in_the_material_box_on_the_shelf.MofasaDB
MofasaDB
The MofasaDB is a publicly available dataset containing 200.000+ de novo generated MOF (Metal-Organic Framework) structures from Mofasa trained on QMOF (up to 170 atoms), along with their geometry-relaxed counterparts. The database is released alongside the paper Mofasa: A Step Change in Metal-Organic Framework Generation. A user-friendly web interface for search and discovery can be accessed at https://mofux.ai/.
Database Overview
The database contains… See the full description on the dataset page: https://huggingface.co/datasets/Orbital-Materials/MofasaDB.hle_material_science
HLE Material Science: A Specialized Benchmark for Materials Science
A Materials Science Subset of Humanity's Last Exam (HLE)
Overview
HLE Material Science is a carefully curated materials science subset derived from the Humanity's Last Exam (HLE) dataset, containing 106 high-quality expert-level questions covering 25+ materials science subfields, with 97% of questions rated as high confidence.
This dataset is designed to evaluate large language models'… See the full description on the dataset page: https://huggingface.co/datasets/TalentZHOU/hle_material_science.MPM-Verse-MaterialSim-Large
MPM-Verse-MaterialSim-Large
Dataset Summary
This dataset contains Material-Point-Method (MPM) simulations for various materials, including water, sand, plasticine, and jelly.
Each material is represented as point-clouds that evolve over time. The dataset is designed for learning and predicting MPM-based
physical simulations. The dataset is rendered using five geometric models - Stanford-bunny, Spot, Dragon, Armadillo, and Blub.
Each setting has 10 trajectories per… See the full description on the dataset page: https://huggingface.co/datasets/hrishivish23/MPM-Verse-MaterialSim-Large.hf_policy_materialsnexus-materialschinese-materials-science-open-intelligence
🔬 Chinese Materials Science & Metallurgy Open Intelligence Dataset
Curated open intelligence dataset providing English research briefs, authoritative DOIs, executive summaries, and high-resolution micrographs of breakthrough Chinese scientific research in Materials Science, Metallurgy, Advanced Alloys, and Mining Engineering.
[!IMPORTANT]
Data Completeness & Research Authenticity Notice:
Included in this Hugging Face Open Dataset: English structured abstracts, core… See the full description on the dataset page: https://huggingface.co/datasets/simpleG2023/chinese-materials-science-open-intelligence.Materials_Project
Cite this dataset Jain, A., Ong, S. P., Hautier, G., Chen, W., Richards, W. D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., and Persson, K. A. Materials Project. ColabFit, 2023. https://doi.org/10.60732/4bf2e346
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_pv1f3dlo5dsc_0
Visit the ColabFit Exchange to search… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/Materials_Project.science_materialsapple-dms-materials
Apple Dense Material Segmentation (DMS) Dataset
A pixel-level material segmentation dataset containing ~41K images with dense annotations across 57 material categories. Originally released by Apple as part of the Dense Material Segmentation (DMS) research project.
Note: This is a mirror prepared for direct use with the HuggingFace 🤗 datasets library. The source images originate from Open Images V7, and material annotations were created by Apple. Some images (~6%) from the original… See the full description on the dataset page: https://huggingface.co/datasets/AllanK24/apple-dms-materials.multi-material-fingerprint-spoofing
Fingerprint Spoofing
The dataset contains over 4,000+ photos from 100 people, consisting of fingerprints images and spoofing attacks created using various spoofing materials such as alginate, plasticine, and silicone. It serves as essential training data for biometric systems focused on fingerprint recognition and spoof detection.
By utilizing this dataset, researchers and developers can advance their understanding and capabilities in biometric security and spoof detection… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/multi-material-fingerprint-spoofing.material-Chroma-dbsec-material-contracts-qa-splittedMixed and filtered version of chenghao/sec-material-contracts-qa and jordyvl/DUDE_subset_100val.
hle_material_science
HLE Material Science: A Specialized Benchmark for Materials Science
A Materials Science Subset of Humanity's Last Exam (HLE)
Overview
HLE Material Science is a carefully curated materials science subset derived from the Humanity's Last Exam (HLE) dataset, containing 106 high-quality expert-level questions covering 25+ materials science subfields, with 97% of questions rated as high confidence.
This dataset is designed to evaluate large language models'… See the full description on the dataset page: https://huggingface.co/datasets/stonelight/hle_material_science.open-materials-guide-0210-embeddingspbr-materials
PBR Materials (MonoRelief V2 core)
Auto-generated PBR material set (10 materials). Each subfolder contains a complete PBR set:
Map
File
Format
Albedo
*_albedo.png
8-bit RGB
Height
*_height.png
16-bit grayscale
Normal
*_normal.png
8-bit RGB (OpenGL, Godot 4)
Roughness
*_roughness.png
8-bit grayscale
Metallic
*_metallic.png
8-bit grayscale
Pipeline
Generated using MonoRelief V2 (Fig. 7), Marigold-only variant:
Base depth — Marigold Depth… See the full description on the dataset page: https://huggingface.co/datasets/Zakhar1746/pbr-materials.materials-project
Dataset
Materials project (2019 dump)
This dataset contains 133420 materials with formation energy per atom.
Processed from mp.2019.04.01.json
Download
Download link: materials-project.tar.gz
MD5 checksum c132f3781f32cd17f3a92aa6501b9531
Content
Bundled in materials-project.tar.gz.
Index (index.json)
list of dict:
index (int) => index of the structure in data file.
id (str) => id of Materials Project.
formula (str) => formula.
natoms (int) => number… See the full description on the dataset page: https://huggingface.co/datasets/materials-toolkits/materials-project.