AI Dataset2011
Provides labeled movie-review data for binary sentiment classification: 25,000 training and 25,000 test examples, plus 50,000 unlabeled reviews for unsupervised or semi-supervised use. Labels reflect strong polarity (positive ≥7, negative ≤4) and the set is a widely used NLP benchmark.
AI Dataset2016
Provides about 100,000 crowd‑written question–answer pairs from Wikipedia where each answer is a text span in the passage, used to train and evaluate extractive question‑answering models. Includes train/validation splits, span offsets, Parquet format, CC BY‑SA 4.0.
AI Dataset2022
Curated English Wikipedia text prepared for language-model training and evaluation, provided in WikiText-2 and WikiText-103 variants. Preserves original case, punctuation and numbers; offers raw and tokenized splits for long-range language modeling under a CC BY‑SA license.
AI Dataset2022
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.
AI Dataset2022
Contains 40,000 teacher-generated reasoning traces distilled from the Qwen3.8-27B model for supervised fine-tuning and analysis. Covers code, math, science and logic; each example pairs a <think> chain-of-thought with a final response and is distributed in JSONL/Parquet for SFT workflows.
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
A public dataset of one million real-world conversations with 25 LLMs, including conversation text, model name, detected language tags, and OpenAI moderation outputs — useful for studying prompt distributions, safety/moderation, and training/evaluating instruction-following models.
AI Dataset2023
Benchmark for evaluating general AI assistants with 466 short, real-world questions that require tool use, multimodality and reasoning; provides a public dev set and a withheld test set used for leaderboard evaluation.
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 Infra2023
Curated learning hub that aggregates roadmaps, tutorials, bootcamps, books, projects, and tool recommendations for learning data engineering and production data infrastructure. Focuses on practical applied learning (projects, interview prep, community links) rather than code libraries.
AI Dataset2023
A multiple-choice benchmark for evaluating LLM understanding in Traditional Chinese across 66 subjects (elementary to professional). Contains ~22K verified questions covering STEM, humanities, social sciences and Taiwan-specific topics, with standardized splits and model leaderboards under an MIT license.