AI Dataset2023
Provides 52,000 English instruction–response pairs generated by OpenAI's text-davinci-003 for instruction-tuning language models. Released under CC BY-NC 4.0; low-cost synthetic data useful for research but contains model-generated biases and errors.
AI Dataset2023
A 15,000+ English instruction–response corpus for fine-tuning and evaluating LLM instruction-following behavior. Contains human-authored prompts and answers across categories (closed/open QA, summarization, extraction, classification, brainstorming) and is released under CC BY-SA 3.0.
AI Dataset2023
Contains short, small-vocabulary stories synthetically generated by GPT-3.5 and GPT-4 for training and evaluating compact language models. Includes multiple splits, a GPT-4-only V2 subset, and archive files with prompts and metadata for reproducible experiments.
AI Dataset2023
Provides a 200k-example filtered conversational dataset derived from UltraChat for supervised fine‑tuning and generation‑ranking of chat models. Stored in parquet with four splits and used as part of Zephyr‑7B‑β training data.
AI Dataset2024
Provides a multilingual, deduplicated corpus of public source code in Parquet for large-scale model training and evaluation. Includes license metadata, language splits, and streaming-friendly packaging for use with Hugging Face Datasets — suited to training code-focused foundation models but requires careful license/provenance review.
AI Dataset2024
Provides 300k annotated multilingual text examples for identifying and masking personally identifiable information (PII) across multiple domains and languages (EN, FR, DE, IT, ES, NL). Intended for training and evaluating token-level PII detection and masking models; includes a DOI for citation.
AI Dataset2024
Provides a cleaned, deduplicated English web corpus optimized for LLM pretraining—over 15T tokens aggregated from CommonCrawl with per-dump snapshots and smaller sampled configs (10B/100B/350B). Includes the datatrove processing pipeline, MinHash deduplication, and an ODC-By v1.0 license; suited for large-scale model training and ablation studies but not specialized for code.
AI Dataset2024
Provides ~1.3 trillion tokens of web pages filtered for educational quality using an LLM-trained classifier; includes per-Crawl configs, smaller random samples (10B/100B/350B tokens), and the classifier code and model for reproducible filtering.
AI Dataset2024
Provides leaderboard-ready test splits for the Open ASR Leaderboard: converts unsafe custom loaders to Parquet, sorts samples by audio length, and packages eight ESB test sets (LibriSpeech, Common Voice, GigaSpeech, SPGISpeech, etc.) for reproducible ASR benchmarking.
AI Dataset2024
Structured dataset for training and evaluating LLM agentic behavior: function-calling conversations, JSON-mode structured outputs, and extraction samples for teaching models to generate tool calls and strict structured responses. Includes single-turn and multi-turn scenarios across several configs.
AI Dataset2024
Provides pre-parsed Parquet snapshots of English and French Wikipedia articles with structured fields (sections, infoboxes, tables, references, images) and credibility signals — optimized for large-scale analysis, retrieval-augmented generation, and model development.
AI Dataset2024
Provides point-accurate annotations of interactive parts in high-resolution indoor laser-scan point clouds, plus affordance labels, motion axes and natural-language task descriptions; includes aligned iPad RGB-D video slices with 2D projections for multimodal research.