datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sec-contracts-financial-extraction-instructions
S&P 500 SEC Financial Extraction Instructions
Dataset Summary
7,683 instruction-tuning examples for training LLMs to extract structured financial data from SEC filings. Covers two filing types across S&P 500 companies:
Split
Examples
Filing Type
Description
train
3,430
Exhibit 10 + DEF 14A
Positive examples with validated outputs
corrective
4,253
Exhibit 10 + DEF 14A
Corrective, rescued, and negative examples
Exhibit 10 — Material Contracts (2… See the full description on the dataset page: https://huggingface.co/datasets/TheTokenFactory/sec-contracts-financial-extraction-instructions.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.legalbench_consumer_contracts_qa
LegalBenchConsumerContractsQA
An MTEB dataset
Massive Text Embedding Benchmark
The dataset includes questions and answers related to contracts.
Task category
t2t
Domains
Legal, Written
Reference
https://huggingface.co/datasets/nguha/legalbench/viewer/consumer_contracts_qa
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["LegalBenchConsumerContractsQA"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/legalbench_consumer_contracts_qa.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.slither-audited-smart-contractsThis dataset contains source code and deployed bytecode for Solidity Smart Contracts that have been verified on Etherscan.io, along with a classification of their vulnerabilities according to the Slither static analysis framework.cuad-pdf-contractsThis dataset contains the contract pdf files from https://huggingface.co/datasets/theatticusproject/cuad
Files present in https://huggingface.co/datasets/theatticusproject/cuad/tree/main/CUAD_v1/full_contract_pdf
are extracted and then uploaded in single bucket without folder heiraarchies.
About CUAD:
CONTRACT UNDERSTANDING ATTICUS DATASET
Contract Understanding Atticus Dataset (CUAD) v1 is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled… See the full description on the dataset page: https://huggingface.co/datasets/ginntonicfun/cuad-pdf-contracts.legal_contractsmailroom-cuad-contracts
Mailroom Eval: Cuad Contracts
Mirror of the Braintrust evaluation dataset mailroom-cuad-contracts from the
llm-entity-extraction
experiment loop (llm-mailroom legal document pipeline).
Field
Value
Rows
50
Source script
stream_cuad_to_bt.py
Braintrust dataset id
c55ac7f0-56ff-4a2c-b968-7f382ce7daea
Braintrust project id
02fb28b9-60e2-40b6-a68a-b72ee0b237ad
Exported (UTC)
2026-08-22T05:03:53+00:00
Export sha256… See the full description on the dataset page: https://huggingface.co/datasets/Lucius-Morningstar/mailroom-cuad-contracts.environment-contracts
geodesic-research/environment-contracts
Local-pipeline snapshot published via --push-from-local (GH #52). All configs below were built locally (Hub-independent) and uploaded in a single commit at one snapshot revision.
Pipeline run params hash: dd13a8843fce63fefa4e70c743f85c6cba30904523b6097a96bfe98100c298eb
Configs in this snapshot: conversation
Per-run provenance: _pipeline_state/dd13a8843fce63fefa4e70c743f85c6cba30904523b6097a96bfe98100c298eb.json (in this repo) and each… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/environment-contracts.Contracts-Ethereum-Cryptocurrency-Data
Contracts-Ethereum-Cryptocurrency-Data
Hive-partitioned Parquet export of BlockDB contracts (Ethereum).
Load
from datasets import load_dataset
ds = load_dataset("RBudzynski/Contracts-Ethereum-Cryptocurrency-Data", split="train")
Files live under data/year=YYYY/month=MM/part-NNNN.parquet.
Range: 2015-08 .. 2026-06 (UTC calendar months).
Schema
column
type
block_timestamp
timestamp
block_number
int64
tx_index
int32
trace_address… See the full description on the dataset page: https://huggingface.co/datasets/RBudzynski/Contracts-Ethereum-Cryptocurrency-Data.all-ethereum-contracts
All ethereum contracts
This dataset contains all deployed Ethereum contracts as of block 21850000 (February 15th, 2025), bytecodes of the contracts, and the block numbers the contracts were deployed.
Contract bytecodes are stored as a hash of the bytecode, and another dataset is provided mapping bytecode hashes to bytecodes. This is to reduce the size of the dataset, as many contracts have identical bytecodes.
This dataset was exported from a PostgreSQL database into CSV format.… See the full description on the dataset page: https://huggingface.co/datasets/Zellic/all-ethereum-contracts.us_contractslegal_contractsThis new dataset is designed to solve this great NLP task and is crafted with a lot of care.sec-material-contracts-qa-splittedMixed and filtered version of chenghao/sec-material-contracts-qa and jordyvl/DUDE_subset_100val.
evm_contracts
EVM Contracts
Description
EVMC (Ethereum Virtual Machine Contracts) is a collection of smart contracts from the ETH blockchain.
In particular, each sample holds the creation and runtime bytecodes.
When available, the sources are also included.
Metadata
homepage: https://github.com/apehex/feedblocks
version: 1.0.1
HEX Dataset
Config
Split
Size
Samples
Blocks
'hex-ethereum'
'train'
2.8 GB
1,294,247
19,493,000 - 20,292,000
'hex-ethereum'… See the full description on the dataset page: https://huggingface.co/datasets/apehex/evm_contracts.us-government-contracts
US Federal Contract Awards
Federal contract actions paid to publicly traded companies — and, for each one,
the day the public could first see it, which for the Department of Defense
is three months after the contract was signed.
12 371 350 contract transactions · 9 552 299 awards · 1 694 listed companies ·
FY2005 to today · $4.41tn obligated
70% of those rows are the Department of Defense and the Army Corps of
Engineers, and not one of them is dated less than ninety-two days… See the full description on the dataset page: https://huggingface.co/datasets/ZipLime/us-government-contracts.sec-contracts-2015-2025
SEC Contracts 2015–2025
Mini corpus of contract text extracted from SEC filings (EDGAR). Includes clause‑level rows with metadata for classification and QA experiments.
usaspending_2024_all_contractsflattened_contractslegal-contractssec-contracts-corrective-extraction
S&P 500 SEC Financial Extractions - Corrective Dataset
Dataset Summary
4,253 corrective instruction-tuning examples designed to teach LLMs what the base model gets wrong when extracting structured financial data from SEC filings. Covers both Exhibit 10 material contracts and DEF 14A proxy statements from S&P 500 companies.
This is a companion to TheTokenFactory/sec-contracts-financial-extraction-instructions, which contains the positive training examples.
Pipeline… See the full description on the dataset page: https://huggingface.co/datasets/TheTokenFactory/sec-contracts-corrective-extraction.contractscrub-repro
ContractScrub reproduction (synthetic variant)
Reproduction of ContractScrub: A benchmark for final review of legal contracts
(arXiv:2608.20204, Thomson Reuters Foundational Research). The official gold
(tri-fair-lab/contract_scrub) was still unreleased at reproduction time, so this
repo contains a method-faithful pipeline + a synthetic benchmark with ground
truth true by construction — not the paper's leaderboard numbers.
Contents
SCORING.md — detailed… See the full description on the dataset page: https://huggingface.co/datasets/arthrod/contractscrub-repro.supply_chain_contracts_dataset_smallreinsurance-contracts-classificationThis dataset contains the full text and the classification of 6671 reinsurance-related documents extracted from SEC filings. The documents include reinsurance contracts, but also ancillary documents, such as amendments, endorsements, extensions, and other documents referring to reinsurance agreement.
The documents have been classified by three language models: qwen3-235b-a22b-2507, gpt-oss-120b and gemini-2.5-flash-lite. Manual inspection of the classification results reveals that qwen3 is… See the full description on the dataset page: https://huggingface.co/datasets/andreaaltomani/reinsurance-contracts-classification.nba-salary-cap-contracts-2016-2026
NBA Salary Cap & Contracts, 2016-2026
An analysis-ready dataset of NBA salaries, payrolls and the salary-cap system over ten seasons (2015-16 baseline through 2025-26, plus a mechanical 2026-27 to 2031-32 projection). It combines player-salary snapshots with the institutional thresholds that govern them: cap, luxury tax, aprons, minimums and the rookie scale.
Published by MrBridge. It backs the study NBA Salaries and Contracts, 2016-2026 on mr-bridge.com.
Files… See the full description on the dataset page: https://huggingface.co/datasets/Mr-Bridge/nba-salary-cap-contracts-2016-2026.us_contractsContractssmart-contracts-instructions
Smart Contracts Instructions
A dataset containing 6,003 GPT-generated human instruction and Solidity source code data pairs.
GPT models used to make this data are GPT-3.5 turbo, GPT-3.5 turbo 16k context, and GPT-4. Solidity source codes are used from mwritescode's Slither Audited Smart Contracts (https://huggingface.co/datasets/mwritescode/slither-audited-smart-contracts).
Distributions of the GPT models used to make this dataset:
GPT-3.5 Turbo: 5,276
GPT-3.5 Turbo 16k Context:… See the full description on the dataset page: https://huggingface.co/datasets/AlfredPros/smart-contracts-instructions.contract_scrub
Coming soon!
uk_ner_contracts_spacy
Dataset Description
Legal Contracts Dataset for Training SpaCy NER Model
This repository contains a specially curated dataset consisting of legal contracts. It is designed for the purpose of training a Named Entity Recognition (NER) model using SpaCy, with the aim to recognize and classify four types of entities in the text:
Contract Type,
Clause Title,
Clause Number,
Definition Title
The dataset includes a broad variety of legal contracts, covering diverse domains such as… See the full description on the dataset page: https://huggingface.co/datasets/lawinsider/uk_ner_contracts_spacy.