datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Rosetta-Activations
Rosetta Activations
Updated: 2026-06-15 02:30 UTC
Contrastive activation extractions for 17 semantic concepts across 46 language models,
supporting cross-architecture mechanistic interpretability research.
Companion concept pair corpus: jamesrahenry/Rosetta_Concept_Pairs
Papers: forthcoming
Dataset Structure
Rosetta-Activations/
├── rcp_v1/ # Current extraction line — richest data (N≈2000)
│ └── {Model_Name}/
│ ├── calibration_{concept}.npy… See the full description on the dataset page: https://huggingface.co/datasets/james-ra-henry/Rosetta-Activations.ResearchClawBench
ResearchClawBench
Evaluating AI Agents for Automated Research from Re-Discovery to New-Discovery
Quick Start | Submit Tasks | How It Works | Domains | Leaderboard | Add Your Agent
ResearchClawBench is a benchmark that measures whether AI coding agents can independently conduct scientific research — from reading raw data to producing publication-quality reports — and then rigorously evaluates the results against real human-authored papers.… See the full description on the dataset page: https://huggingface.co/datasets/InternScience/ResearchClawBench.real-toxicity-prompts
Dataset Card for Real Toxicity Prompts
Dataset Summary
RealToxicityPrompts is a dataset of 100k sentence snippets from the web for researchers to further address the risk of neural toxic degeneration in models.
Languages
English
Dataset Structure
Data Instances
Each instance represents a prompt and its metadata:
{
"filename":"0766186-bc7f2a64cb271f5f56cf6f25570cd9ed.txt",
"begin":340,
"end":564,
"challenging":false… See the full description on the dataset page: https://huggingface.co/datasets/allenai/real-toxicity-prompts.RoboPulsePlusPlus
RoboPulse++
RoboPulse++ is an interval-level benchmark introduced in PRM-as-a-Judge 1.5: A Toolkit for Robot Process Assessment for evaluating progress judge models throughout complete robot manipulation trajectories.
This Hugging Face release contains 700 episodes with natural-language task instructions, temporally ordered observations, and human-annotated progress intervals.
Overview
RoboPulse++ extends progress judging from isolated state pairs to temporal… See the full description on the dataset page: https://huggingface.co/datasets/lyy0715/RoboPulsePlusPlus.arena-resultsThis dataset contains the saved results from MTEB-Arena
soc-builder-rtl-v1
SoC Builder RTL Dataset — v1 (Experiment Release)
A reproducible, machine-generated corpus of synthesizable System-on-Chip (SoC) RTL designs for machine learning on hardware: RTL representation learning today, and — as the corpus grows — netlist, timing, and placement prediction. Every design is a complete, hierarchical, lint-clean Verilog SoC assembled from real open-source IP — RISC-V CPU cores, network-on-chip (NoC) interconnects, accelerators, peripherals, memories and… See the full description on the dataset page: https://huggingface.co/datasets/hasankursun/soc-builder-rtl-v1.faience-games
Faïence: human-vs-net Azul games
Every game played on Faïence, a
free browser implementation of the rules of Azul (Michael Kiesling) against
a neural net trained by self-play, unless the player switched sharing off.
This dataset is the training pile the playing page tells its players about,
and it is public precisely so that a player can read everything the project
collects. Records are anonymous by construction: moves, deals, which net
played, and the score. No names, no… See the full description on the dataset page: https://huggingface.co/datasets/RemiFabre/faience-games.irish_fineweb_eduData translation project of https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu, sample-10BT subset. Data are translated from English to Irish using NLLB-3.3B.
Audio2Tool
Audio2Tool: Speak, Call, Act — A Dataset for Benchmarking Speech Tool Use
Authors: Ramit Pahwa1,∗,∗∗, Apoorva Beedu1,∗, Parivesh Priye1, Rutu Gandhi†1, Saloni Takawale†1, Aruna Baijal1, Zengli Yang1
1 Rivian & Volkswagen Technologies · ∗ equal contribution · ∗∗ corresponding author · † equal contribution
📄 Project page / demo: https://audio2tool.github.io/
📦 Dataset: https://huggingface.co/datasets/RVtech/Audio2Tool
✉️ Contact (corresponding… See the full description on the dataset page: https://huggingface.co/datasets/RVtech/Audio2Tool.proof-bundlesregx-benchmark
RegX
Cross-Domain Multi-View Point Cloud Registration Benchmark
RegX evaluates multi-view point cloud registration across scales spanning nine orders
of magnitude — nanometre-scale microscopy to kilometre-scale airborne maps — and sensors
never designed to be compared: clinical colonoscopes, RGB-D cameras, spinning and
solid-state LiDAR, terrestrial and airborne laser scanners.
Most registration benchmarks fix one sensor and one scale. RegX asks a narrower question
instead: does… See the full description on the dataset page: https://huggingface.co/datasets/YuePanEdward/regx-benchmark.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/G4KMU/t2-ragbench.SlimPajama-Meta-rater
Annotated SlimPajama Dataset
Dataset Description
This dataset contains the first fully annotated SlimPajama dataset with comprehensive quality metrics for data-centric large language model research. The dataset includes approximately 580 billion tokens from the training set of the original SlimPajama dataset, annotated across 25 different quality dimensions.
Note: This dataset contains only the training set portion of the original SlimPajama dataset, which is why the… See the full description on the dataset page: https://huggingface.co/datasets/opendatalab/SlimPajama-Meta-rater.rte
Glue RTE
This dataset is a port of the official rte dataset on the Hub.
Note that the sentence1 and sentence2 columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
ps4mas-final-test-rollouts-0813
PS4MAS Final Test Rollouts (0813)
Source split: ps4mas-0521-splits final_test_scenarios.jsonl
Each traces/<model>/<model>.jsonl contains the agent-tool-loop output for 200 final_test scenarios × 4 topologies. Most baseline/oracle files are raw traces. GiGPO 0805-r2 step20/40/60/80 evals include OSS-120B scores and summary.json.
Files
Model
Rows
Path
best_rl_gigpo_debate_step40
800
traces/best_rl_gigpo_debate_step40/best_rl_gigpo_debate_step40.jsonl… See the full description on the dataset page: https://huggingface.co/datasets/yinita/ps4mas-final-test-rollouts-0813.total-300-random-jh-epoch4
total-300-random-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.440625
Valid samples: 320/320
document-review-data
Document Review Data
Private dataset for the Office/PDF title extraction review app and the current extractive title-training data package.
Current Title Extraction Dataset Surface
Canonical prefix:
datasets/title_extraction/
Effective datasets:
datasets/title_extraction/training/source4k_device_qwen_fp1000_v1/
datasets/title_extraction/evaluation/real_device_280_v1/
datasets/title_extraction/synthetic/controlled_synthetic_parse_v1/
The Dataset Viewer is… See the full description on the dataset page: https://huggingface.co/datasets/mannycooper/document-review-data.nla-av-responses-llama-70b-layer53total-131-lambda02-residual-s_signal_type6-jh-epoch4
total-131-lambda02-residual-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3765625
Action score: 0.4171875
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-retry-epoch4
total-300-lambda02-s_signal_type6-jh-retry-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.36953125
Action score: 0.3984375
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
total-300-lambda02-s_signal_type6-jh-epoch4-reeval2
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4125
Action score: 0.4265625
Valid samples: 320/320
qwen35-4b-reeval3
qwen35-4b-reeval3
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3859375
Action score: 0.4125
Valid samples: 320/320
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
total-300-lambda02-s_signal_type6-jh-epoch4-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38828125
Action score: 0.4234375
Valid samples: 320/320
qwen35-4b-reeval2
qwen35-4b-reeval2
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.384375
Action score: 0.4265625
Valid samples: 320/320
qwen35-4b-reeval1
qwen35-4b-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.39296875
Action score: 0.4203125
Valid samples: 319/320
appworld-qwen35-4b-agent-rl-epoch3
appworld-qwen35-4b-agent-rl-epoch3
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.45859375
Action score: 0.475
Valid samples: 320/320
qwen35-4b-reeval4
qwen35-4b-reeval4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3984375
Action score: 0.4265625
Valid samples: 319/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.40546875
Action score: 0.475
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4046875
Action score: 0.4703125
Valid samples: 320/320
appworld-qwen35-4b-agent-rl-epoch3-reeval1
appworld-qwen35-4b-agent-rl-epoch3-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4578125
Action score: 0.4921875
Valid samples: 320/320