Provides a reproducible, deduplicated corpus of text extracted from PDFs for LLM pretraining—about 3 trillion tokens from ~475 million documents in 1733 language-script pairs. Includes OCR and text extraction pipelines, per-page language IDs, MinHash deduplication, and is released under ODC‑By 1.0.
[next-mdx-remote-client] error compiling MDX: Unexpected character `2` (U+0032) before name, expected a character that can start a name, such as a letter, `$`, or `_` More information: https://mdxjs.com/docs/troubleshooting-mdx
Provides 2,000 synthetic multiple-choice items designed for continuation log-likelihood scoring to evaluate small language models' Theory of Mind (social-cognitive) abilities; 40 constructs, balanced answer positions, and easy/medium difficulty.
Provides 5.5K+ self-contained data-analysis RL tasks: each row bundles a real tabular dataset, a question, and a deterministically-gradable gold answer. Verified from jupyter-agent notebooks; splits for training, held-out testing, and quick eval; intended for prompting, fine-tuning, and agent RL.
Provides mixed-domain, verifiable RL training environments for LLM agents (code, cyber, knowledge work, web dev, music) as Parquet datasets, with domain-specific verifiers, Docker artifacts and links to training code for reproducible agentic RL experiments.
