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Contains 73 images used in Hugging Face library documentation, packaged in Parquet and imagefolder formats for examples, demos, and small-scale image experiments; distributed under CC BY‑NC‑SA 4.0.
A 12K-question multiple-choice benchmark that raises difficulty by expanding choices to ten and adding reasoning-focused problems. Designed for robust LLM evaluation with cross-domain coverage, expert curation, and emphasis on chain-of-thought performance.
A monthly-updated, hive-partitioned parquet corpus of billions of standard rated chess games from Lichess for data analysis and ML — includes move lists with clock info, player Glicko2 ratings, openings, timestamps, and some Stockfish evals under CC0.
A fine-grained, domain-labeled web corpus for NLP and LLM research that decomposes a deduplicated web crawl into 67 domains via iterative URL/content labeling and coarse→fine recall; includes per-domain statistics, validation subsets, and domain-benchmark analysis tools.
Turns human desktop demonstrations into training data for agents that reason over screenshots and control mouse and keyboard. Releases a cross-OS collection tool, AgentNet data, and models; the paper reports 45.0% on OSWorld-Verified for its 72B model.
Charting engine and interpretation dataset for Zi Wei Dou Shu (Purple Star Astrology): deterministic natal chart algorithm, Four Transformations, pattern rules, and large v3/v4 interpretation datasets. Code MIT and data CC BY 4.0; judgment library and AI backend are closed.
Generates computer-use tasks with executable setups and verifiable rewards. A generator and independent reward writer produce 32,112 verified examples across 110 desktop and mock-web environments for reinforcement learning.
Generates articulated motion for arbitrary rigged 3D skeletons from text prompts with a single unified model and no per-skeleton retraining. Uses topology-aware diffusion-transformer architecture and a large UniML3D motion dataset to generalize across bipeds, quadrupeds, and other topologies; suitable for text-to-animation workflows and rapid prototyping.
Selected ~245B-token corpus of algorithmically relevant code across 11 languages from The Stack v3, produced by file-level language-adaptive selection (UltraData-Code-L2-Classifier). Concentrates problem-solving implementations for LLM code pretraining while preserving broad language coverage; released under ODC-By.
Provides 22 curated Three.js-based cases for code-guided video generation across eight application categories. Each case bundles an editable scene (Three.js program), a 960×544 proxy video, a 1536×864 reference image, and a plain-text prompt for controlled video-generation evaluation.
A multimodal supervised fine‑tuning corpus for training MLLMs: 44.3M samples (100.3M QA pairs) over 19.7M image groups, annotated with short/long chain‑of‑thought and produced by rerunning the HoneyPipe curation pipeline with multi‑model rollouts and verifications.
Provides 130,000 typed RAG claim-verification decisions that pair source-derived reference labels with jev-1.13.0 model predictions. Includes sentence/span grounding, hallucination-type presence, whole-response grounding and response-quality decisions with retained provenance. Suited for grounding error analysis, prototype evidence-checkers and confidence-threshold studies; license: other.