AI Dataset2026
Provides per-cell transcriptomes and five-day drug-sensitivity readouts for 1.83M single cells across 52 cancer cell lines and 91 drug conditions, with raw counts plus gene, cell-line, drug, and summary metadata for modeling drug response and context-dependent gene function.
AI Dataset2026
Provides the gated, official OSWorld 2.0 Python task class files (task_*.py) required to run the benchmark; distributed via a Hugging Face gated dataset to reduce benchmark leakage. Download requires accepting gated access on Hugging Face.
AI Dataset2026
Benchmark dataset for evaluating long-horizon coding agents and software-engineering tasks, containing English code and tabular metadata in Parquet format; small scale (<1K examples) for fast prototyping and evaluation.
AI Dataset2026
Provides 500+ hours of human whole-body teleoperation recordings of a Unitree G1 in real homes, packaged in LeRobot v3.0 for robot learning. Contains 23K+ episodes, ~40M frames, multi-view 480p@30 video, 29-DoF states, actions and language annotations; CC BY 4.0 and large download size.
AI Dataset2026
Contains a sanitized Claude Code (Fable 5) JSONL transcript of a session that procedurally built a Boeing 747 in Three.js, including assistant messages, tool calls, and base64 screenshots — useful for studying agent trace, tool use, and vision self‑verification workflows.
AI Dataset2026
Refines large-scale English pretraining corpora by predicting per-instance structured edits (insert, delete, replace) and deterministically applying them to produce cleaner text for LLM training. Provides five ~20B-token refined corpora in parquet with edit metadata and simple loading configs.
AI Dataset2026
Benchmark for evaluating multimodal LLM safety in Korean cultural contexts — includes KSAFE-MM-G which localizes global safety queries into Korean scenarios and KSAFE-MM-C which targets culture-specific visual-textual vulnerabilities. Provides curated image–text pairs and jailbreak-style prompts to reveal both unsafe behaviors and over-refusal.
AI Dataset2026
Provides kanji-level evaluation data for Japanese TTS: disambiguated sentence contexts targeting 4,378 kanji-reading pairs (2,136 Jōyō kanji) with 13,095 native-speaker–verified sentences and katakana-marked ground-truth readings for kanji-level error metrics.
AI Dataset2026
Collects raw coding-agent sessions—developer prompts, model replies, tool calls, and command output—donated from public repositories and anonymized locally. Organized by agent harness (raw session files + Parquet table), useful for studying agent behavior and tool use; anonymization is best-effort.
AI Dataset2026
A JSON dataset of ~1.1M anonymized coding-assistant instruction→response interactions for training and evaluating code-generation and instruction-following models; packaged for use with pandas/polars and sized at ~459 MB.
AI Dataset2026
Curates ~1.1M instruction–response examples for 'vibe coding' scenarios where developers prompt LLMs to produce implementation plans, architecture choices, and deployment steps. Covers conversation memory, prompt templates, model routing, streaming responses, and scaling considerations; Apache-2.0.
AI Dataset2026
A JSON-format text dataset of 'vibe-coding' prompt–response examples sized in the 1M–10M category. Packaged for Hugging Face Datasets with pandas/polars-ready structure; useful for fine-tuning or evaluation but lacks an explicit license and detailed provenance.