AI Dataset2025
A large multi-config collection of query–document pairs assembled to reproduce and extend the mGTE/LateOn data recipe for pre-training text embedding models. Data come in source-specific configs and include per-row drop/duplicate flags and guidance for using cleaned subsets for training.
AI Dataset2025
A 1,000,000-sample Vietnamese historical conversation dataset in ShareGPT/ChatML format for question-answering and text-generation. Approximately 78% of samples include step-by-step reasoning chains; remaining samples are final-only. Useful for training or evaluating Vietnamese LLMs and chat agents.
AI Dataset2025
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.
Compares standard human psychometric questionnaires (PVQ, BFI) with generation‑based profiling to test whether questionnaires predict real LLM responses. Finds big divergences: questionnaires exploit lexical cues and elicit alignment‑consistent answers, mischaracterizing LLM behavior on everyday queries.
AI Model2025
Turns clinical text into structured, de-identified clinical signals—entity extraction and PII de-identification—that run entirely on local hardware. Provides 1,000+ specialized medical NER models, multilingual support, Apple MLX acceleration, and Apache‑2.0 licensing.
AI Dataset2025
Provides mined hard negatives and relevance scores for 1.88M queries across seven retrieval datasets, enabling contrastive fine-tuning and nv-retrieve filtering; includes full 2048 mined negatives per query, paired query/document splits, and parquet-formatted files for large-scale training.
AI Dataset2025
Open synthetic corpus for training small reasoning-focused language models — ~79.65M generated samples (≈75B tokens with Pleias tokenizer) amplified from ~58.7k Wikipedia/Wikibooks seeds; includes explicit synthetic reasoning traces, multilingual coverage, and parquet splits.
AI Dataset2025
Aggregates SEC EDGAR filings into raw files, parsed plaintext, and rich filing metadata for LLM training and retrieval. Includes ~8.05M filings (~590 GB, ~43B tokens), per-filing token counts, and parsed outputs; Apache-2.0.
AI Client2025
Generates summaries from URLs, YouTube videos, podcasts, PDFs, and local audio or video files. Backend-agnostic by design: the same pipeline drives local coding CLIs (Claude, Codex, Gemini) or hosted API providers (OpenAI, Google, xAI).
AI Client2025
Provides a plug-and-play inference engine that lets language models programmatically inspect, decompose, and recursively call themselves to handle very long contexts; supports local and cloud REPL sandboxes, multiple LLM backends, and trajectory logging/visualization.
AI Dataset2026
Provides open ASR and TTS speech data for 24 Sub‑Saharan African languages to train and evaluate speech models. Includes ~1,250 hours of transcribed ASR and ~235 hours of single‑speaker TTS with train/validation/test/unlabeled splits and mixed CC-BY licenses.
AI Dataset2026
Processed, multilingual news corpus of 1.357B articles extracted from Common Crawl CC‑News with per-article WARC provenance. Includes trafilatura-extracted bodies, language labels (GlotLID & CommonLingua), IPTC topic tags, monthly Parquet shards and a companion FM-index for sub-10ms substring queries; bulk text access is gated for academic research.