datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
m_arc
Multilingual ARC
Dataset Summary
This dataset is a machine translated version of the ARC dataset.
The Icelandic (is) part was translated with Miðeind's Greynir model and Norwegian (nb) was translated with DeepL. The rest of the languages was translated using GPT-3.5-turbo by the University of Oregon, and this part of the dataset was originally uploaded to this Github repository.
SCPWiki-Cleaned-PDF-Archivesrl-run-archive-2026
RL run archive 2026
Archived raw run artifacts (rollout trajectories, rendered frames, policy and optimizer
checkpoints, configs, logs) from simulation reinforcement-learning experiments, published for
long-term preservation and reproducibility.
Layout mirrors the verified backup trees they were copied from:
tilde/20260915-102000/ and taurus/20260915-085631/: batched tar archives. Every archive
carries a per-file SHA-256 manifest inside it; the batch inventories (9998.json.gz… See the full description on the dataset page: https://huggingface.co/datasets/gavinlaw/rl-run-archive-2026.github_archive
GitHub Archive
Description
According to GitHub’s terms of service, issues and pull request descriptions—along with the their comments—inherit the license of their associated repository.
To collect this data, we used the GitHub Archive’s public BigQuery table of events to extracted all issue, pull request, and comment events since 2011 and aggregated them into threads.
The table appeared to be missing “edit” events so the text from each comment is the original from when… See the full description on the dataset page: https://huggingface.co/datasets/common-pile/github_archive.stream-archive
stream-archive
Twitch and Kick chat logs from Italian streamers.
Streamers
Twitch.com (39)
aladinottv, alisonrevenge, arkanightlive, bartopanzer, billybella_, dankol83, dariomocciatwitch, davidrubino, diariodelrusso, enkk, federicacasula_, fufflix, grenbaud, gskianto, homyatol, ilgabbrone, ilrossopiubelloditwitch, immortale____, kasumisen, lollolacustre, lucakingm, luiskant690, macchiativincenzo_babbohs, marcomerrino, menestointhailandia… See the full description on the dataset page: https://huggingface.co/datasets/deplana/stream-archive.Nemotron-SFT-ARC-AGI-v1
Dataset Description:
Nemotron-SFT-ARC-AGI-v1 is a supervised fine-tuning (SFT) dataset of multi-turn agentic reasoning traces produced by open-weight large language models attempting to solve ARC-AGI visual-reasoning puzzles. Each ARC puzzle (a set of (input grid, output grid) demonstration pairs plus one or more test inputs, where grids are 2D integer arrays representing colors) is formatted as a text prompt and given to an agent powered by one of nine open-weight reasoning… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-ARC-AGI-v1.arc-agi-2glenans-isobars-archivearc_easyarc-agi3-kimi-k2.7-ar25
ARC-AGI-3 ar25 — Agent Trajectories (kimi-k2.7)
Gameplay trajectories from the harness×model pair kimi-k2.7 playing the
ARC-AGI-3 game ar25, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same game played by… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-kimi-k2.7-ar25.corpus-archive
corpus-archive
[!WARNING]
Experimental Dataset Architecture: The repository structure, metadata tiers, category taxonomies, and catalog indexing formats are currently under active design and evaluation. All specifications, metadata keys, and JSON schemas detailed below represent representational examples and intended targets.
This repository serves as a structured digital textual archive preserving Hmar literature, historical accounts, school textbooks, dictionaries, parallel… See the full description on the dataset page: https://huggingface.co/datasets/hmar-heritage-org/corpus-archive.arc_challenge_mtMachine translated arc_challenge datasets.
Translated with DeepL.
tcl2-disk-archive
tcl2-disk-archive
Redundant data archived from the tcl2 Vast box before local deletion.
Status: placeholder (2026-09-15). Content is being added in verified batches.
Layout (planned)
MANIFEST.jsonl - one JSON line per archived item: local_path, repo, path_in_repo, bytes, sha256, n_files, encrypted, verified_remote, verified_download, deleted_utc.
Tar archives of PNG trees (per-file md5 lists kept in the manifest side files).
*.tar.enc - third-party-derived data… See the full description on the dataset page: https://huggingface.co/datasets/MingzhenL/tcl2-disk-archive.USCode-QAPairs-Finetuning
USCode-QueryPairs Dataset
This dataset contains query-answer pairs curated from the United States Code, suitable for fine-tuning any embedding model. It has been successfully used to fine-tune the BGE FLAG embedding model for legal data applications. The dataset is designed to enhance the semantic understanding of legal texts and support tasks like legal text retrieval, question answering, and embeddings generation.
Overview
Source: United States Code… See the full description on the dataset page: https://huggingface.co/datasets/ArchitRastogi/USCode-QAPairs-Finetuning.arc_challengearc-agi3-agy-gemini3.1pro-tr87
ARC-AGI-3 tr87 — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game tr87, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-tr87.github_archive_filtered
GitHub Archive
Description
According to GitHub’s terms of service, issues and pull request descriptions—along with their comments—inherit the license of their associated repository.
To collect this data, we used the GitHub Archive’s public BigQuery table of events to extract all issue, pull request, and comment events since 2011 and aggregated them into threads.
The table appeared to be missing “edit” events so the text from each comment is the original from when it was… See the full description on the dataset page: https://huggingface.co/datasets/common-pile/github_archive_filtered.Nemotron-RL-ARC-AGI-v1
Dataset Description:
Nemotron-RL-ARC-AGI-v1 is a reinforcement-learning (RL) gym environment dataset of single-step ARC-AGI puzzle prompts intended for RL post-training of large language models. Each row corresponds to one ARC puzzle (a set of (input grid, output grid) demonstration pairs plus a single test input grid) rendered as a text prompt; reward is binary (1.0 / 0.0) determined by exact-match comparison against the ground-truth output grid. No LLM judge is used, no… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-ARC-AGI-v1.arc-agi3-agy-gemini3.1pro-g50t
ARC-AGI-3 g50t — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game g50t, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-g50t.razavi-benchRazavi-bench
An expert-curated benchmark for analog-design reasoning.
Razavi-bench packages the question-answer assessments from Behzad Razavi's
Analog Design Experiments With AI Part 1 and Part 2 into a clean
one-task-per-directory benchmark. The tasks probe whether a model can reason
about MOS devices, small-signal circuits, feedback, oscillators, comparators,
dividers, LNAs, TIAs, and LC oscillators.
Each task directory keeps only the benchmark prompt, figure, and curated… See the full description on the dataset page: https://huggingface.co/datasets/Arcadia-2026/razavi-bench.MoS-Experiment-Data-Archive
MoS Experiment Data Archive
Public data archive for the DFlash / Aurora MoS experiments.
Contents:
dom250k/ and dom250k_train/: domain-specialist training data.
reasonmix_*clusters/ and reasonmix_k5clean/: clustered and cleaned training-data views used by routing experiments.
natclusters/: natural-cluster data view.
gen800k/: current 800K large-data experiment inputs. This copy remains on Weka until the active 800K experiment is complete.
Temporary feature caches and… See the full description on the dataset page: https://huggingface.co/datasets/ryan-0608/MoS-Experiment-Data-Archive.arc-agi3-agy-gemini3.1pro-su15
ARC-AGI-3 su15 — Agent Trajectories (agy-gemini3.1pro)
Gameplay trajectories from the harness×model pair agy-gemini3.1pro playing the
ARC-AGI-3 game su15, part of the
ARA-as-world-model generalization experiment. The agent builds a structured world model
(an Agent-Native Research Artifact) live during play and consults it to crack levels it
cannot solve from cold exploration.
One dataset repo per harness×model×game: sibling repos
arc-agi3-<harness>-<model>-<game> hold the same… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/arc-agi3-agy-gemini3.1pro-su15.agent-data
Agent Data is designed for training AI agents, particularly in the domain of function calling and multi-turn conversations. It combines four distinct datasets - and is the exact mixture we used when training Arcee-Agent.
Dataset Components
Glaive Function Calling v2
Notable feature: We have synthetically extended ~20k samples with sequential tool calls within the same response.
Salesforce xlam Function Calling
Internlm's Agent-Flan series
Magpie Pro 300k
Magpie is… See the full description on the dataset page: https://huggingface.co/datasets/arcee-ai/agent-data.The-Tome
The Tome is a curated dataset designed for training large language models with a focus on instruction following. It was used in the training of our Arcee-Nova/Spark models, which was later merged with Qwen2-72B-Instruct (or 7B with the Spark model).
Dataset Composition
Total Samples: 1.75 million
Source: Compiled from 9 publicly available datasets
The Tome is comprised of the following datasets:
arcee-ai/infini-instruct-top-500k (BAAI/Infinity-Instruct)… See the full description on the dataset page: https://huggingface.co/datasets/arcee-ai/The-Tome.ro_arc_challenge
Dataset Description
ARC is a dataset of 7,787 genuine grade-school level, multiple-choice science questions assembled to encourage research in
advanced question-answering.
Here we provide the Romanian translation of the ARC Challenge Set from the paper "Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback" (Lai et al., 2023).
This dataset is used as a benchmark and is part of the evaluation protocol for Romanian… See the full description on the dataset page: https://huggingface.co/datasets/OpenLLM-Ro/ro_arc_challenge.uhura-arc-easy
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/ebayes/uhura-arc-easy.uhura-arc-easy
Dataset Card for Uhura-Arc-Easy
Dataset Summary
Uhura-ARC-Easy is a widely recognized scientific question answering benchmark composed of multiple-choice science questions derived from grade-school examinations that test various styles of knowledge and reasoning.
The original English version of the benchmark originates from Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge (Clark et al., 2018) and is divided into "Challenge" and "Easy"… See the full description on the dataset page: https://huggingface.co/datasets/masakhane/uhura-arc-easy.Technical-Architectures-Large
Technical Architectures Large (294k Samples)
Overview
Generating complex, syntactically valid diagram code from natural language requirements is a major challenge for AI models. This dataset bridges that gap by providing over 293,000+ distinct enterprise software architectures generated using two cutting-edge models: GPT-OSS-120B and Qwen3-Coder-Next-FP8.
Unlike simple "toy" examples, these architectures model realistic enterprise systems complete with client… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Technical-Architectures-Large.ARC-Bench
ARC-Bench: An Open-Ended Autonomous-Research Benchmark Across Five Scientific Domains
The benchmark released with AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration.
ARC-Bench is a 55-topic, open-ended autonomous-research benchmark spanning
five scientific domains. Each topic is not a fixed-input/fixed-output task — it is a
research question plus a structured briefing. A research agent (or a human) must
take a topic from question →… See the full description on the dataset page: https://huggingface.co/datasets/AIMING-Lab-UNC/ARC-Bench.arc-steps
ARC Intermediate Solving Steps (arc-steps)
This dataset accompanies the paper TraceViT: Grounded Trace Supervision for Visual Abstract Reasoning.
1,286,952 procedurally generated ARC-style records — 1,062,561 of them
with intermediate solving steps. Each record is an {input, steps, output} triple:
steps is a sequence of intermediate grids tracing a semantically meaningful solution
path from the input to the output, captured at human-annotated checkpoints of the
program that… See the full description on the dataset page: https://huggingface.co/datasets/lbn32/arc-steps.