datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
TRUEBench
TRUEBench: A Benchmark for Assessing LLMs as Human Job Productivity Assistants
TRUEBench is a benchmark introduced by Samsung Research to evaluate the performance of large language models (LLMs) as human job assistants which consists of over 2,400 realistic and challenging samples.
To assess performance in real-world applications, TRUEBench includes diverse dialog scenarios and language conditions.
Main Features
Multilinguality: The user instructions are written in a… See the full description on the dataset page: https://huggingface.co/datasets/SamsungResearch/TRUEBench.solidity-audit-cot
solidity-audit-cot
Long-CoT audit traces for Solidity contracts, generated by Claude Opus 4.7 (adaptive thinking, xhigh effort) over the spec→contract corpus from the Qwopus3.6-27B-solidity training pipeline.
This dataset is the Stage 2 training corpus for the multi-stage Qwopus3.6-27B-solidity model — designed to teach long-form security reasoning (8-15 paragraph chain-of-thought) anchored to real Solidity contracts.
Why this dataset exists
Public Solidity audit… See the full description on the dataset page: https://huggingface.co/datasets/samscrack/solidity-audit-cot.solidity-cpt-top10-quality
Solidity CPT Top-10% Quality-Filtered Corpus
A curated, deduplicated corpus of 23,471 modern Solidity source files (~86M tokens) intended for continued-pretraining (CPT) of code LLMs on smart-contract code.
It's the top 10% slice (by composite quality score) of a larger raw corpus that combined:
ASSERT-KTH/DISL — 514 k unique deployed Solidity files, deduped at file level
30 hand-picked GitHub blue-chip protocols (OpenZeppelin, Uniswap v2/v3/v4, Aave v3, Compound, Morpho… See the full description on the dataset page: https://huggingface.co/datasets/samscrack/solidity-cpt-top10-quality.task1572_samsum_summary
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1572_samsum_summary
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1572_samsum_summary.VoiceAssistant-Eval
🔥 VoiceAssistant-Eval: Benchmarking AI Assistants across Listening, Speaking, and Viewing
[🌐 Homepage]
[🔮 Visualization]
[💻 Github]
[📖 Paper]
[📊 Leaderboard ]
[📊 Detailed Leaderboard ]
[📊 Roleplay Leaderboard ]
🚀 Data Usage
from datasets import load_dataset
for split in ['listening_general', 'listening_music', 'listening_sound', 'listening_speech',
'speaking_assistant', 'speaking_emotion', 'speaking_instruction_following'… See the full description on the dataset page: https://huggingface.co/datasets/SamSoko83/VoiceAssistant-Eval.solidity-eval-2026
Solidity Eval (2026)
Agentic Solidity benchmark. Each task hands the agent a Foundry workspace where one function body in a real Etherscan-verified contract has been replaced with revert("TODO");. The agent edits, builds (forge build), and tests (forge test) inside a sandbox until it returns. Reward is the differential-fuzz pass rate (Diffusc + Echidna) of the model's body against the ground-truth body.
This dataset is intended for use with the hermes-agent Solidity Eval environment… See the full description on the dataset page: https://huggingface.co/datasets/samscrack/solidity-eval-2026.task1573_samsum_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1573_samsum_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1573_samsum_classification.F24-FFH-VerilogVerilog Generation training dataset - owned and maintained by Samuel Bush via the Secure and Trustworthy Hardware (SETH) Lab at Texas A&M University
Metrics:
Total Rows: ~222,000
Size of .JSON dataset: 17.8GB