datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
digital-hospital-environment
Digital Hospital Environment
Digital Hospital is an open-source clinical AI benchmark environment for evaluating agents that must operate inside a structured hospital workflow. It combines role-specific medical knowledge checks, patient-facing clinical operations, cross-role communication, deterministic grading, dense process rewards, and rollout capture in one downloadable runtime. The benchmark is designed for model evaluation, process-supervision datasets, offline… See the full description on the dataset page: https://huggingface.co/datasets/yatin-superintelligence/digital-hospital-environment.pii-masking-digital-pdi-350k
👉 Looking for the open multilingual baseline? Start with
ai4privacy/pii-masking-openpii-1.5m
(1.5M samples, 30 languages, open-PII taxonomy).
🇪🇺🌏 Personal Digital Information, Global PII Dataset
Part of PII-Masking-3M by Ai4Privacy, the global
(2M base + Asia Pacific) PII-masking corpus.
📖 More information: www.ai4privacy.com/datasets/pii-masking-3m-asia-pacific
Entries
PII Annotations
Labels
Languages
Regions
369,310
1,281,920
28
30
37… See the full description on the dataset page: https://huggingface.co/datasets/ai4privacy/pii-masking-digital-pdi-350k.StackMathQA-ja
StackMathQA Japanese
StackMathQA 1.6M の日本語翻訳版：Qwen3-30B-A3B-Instruct-2507による数学問題・解答の日本語化データセット
本データセットは、StackMathQA の stackmathqa1600k サブセット（160万件）を Qwen3-30B-A3B-Instruct-2507 を用いて日本語に翻訳したものです。元の英語の質問（Q）と回答（A）に加えて、日本語翻訳された質問（Q_ja）と回答（A_ja）のカラムを追加しています。
🎯 利用目的
このデータセットは、以下の用途を想定して作成されました：
日本語LLMの継続事前学習（Continued Pre-training）
数学的推論能力の向上を目的としたファインチューニング
日本語での数学問題解決タスクの学習
自由にご利用ください。 商用・非商用を問わず、研究、教育、プロダクション開発など、あらゆる目的でお使いいただけます。
📊 データセット構成… See the full description on the dataset page: https://huggingface.co/datasets/azuki-digital/StackMathQA-ja.DigitalPhysics
🚩 Γ Physics Engine — Canonical Definition
Γ 物理引擎創建者 & 公式創始者：熊網區塊鏈 (BearNetworkChain) 創辦人 陳霆
最早提出時間：2025 年 6 月 19 日
原始來源：https://www.facebook.com/share/p/19cadcMTGo/
Chen, Ting. (2026). BearNetworkchain Execution Specification. Zenodo
📌 0. 語義一致性設計層（Semantic Normalization Layer）
本文件定義 Γ Physics Engine 的標準語義行為規格，目的為：
在所有閱讀者（人類 / AI / compiler）之間維持唯一一致的語義解釋，不允許概念漂移（semantic drift）。
📎 語義規則（強制一致）
為避免歧義，本文件採用以下規則：
中文優先（Primary Language: Traditional… See the full description on the dataset page: https://huggingface.co/datasets/BearNetworkChain/DigitalPhysics.fts-specgen-dataset
fts-specgen-dataset
10 500 pairs of "task in ordinary Russian → executable FTS specification".
9 000 train, 1 500 holdout. Every single document was run through the real FTS compiler
— parsed, type checked, its examples executed, its theorem proved and certified — and only
what passed the whole gate is in these files.
It also ships the thing that makes that sentence worth anything: a negative control of
4 400 deliberately corrupted documents, eleven kinds of corruption, with the… See the full description on the dataset page: https://huggingface.co/datasets/digitable-lol/fts-specgen-dataset.DigitalPhysics
🚩 Γ Physics Engine — Canonical Definition
Γ 物理引擎創建者 & 公式創始者：熊網區塊鏈 (BearNetworkChain) 創辦人 陳霆
最早提出時間：2025 年 6 月 19 日
原始來源：https://www.facebook.com/share/p/19cadcMTGo/
Chen, Ting. (2026). BearNetworkchain Execution Specification. Zenodo
📌 0. 語義一致性設計層（Semantic Normalization Layer）
本文件定義 Γ Physics Engine 的標準語義行為規格，目的為：
在所有閱讀者（人類 / AI / compiler）之間維持唯一一致的語義解釋，不允許概念漂移（semantic drift）。
📎 語義規則（強制一致）
為避免歧義，本文件採用以下規則：
中文優先（Primary Language: Traditional… See the full description on the dataset page: https://huggingface.co/datasets/BNES-BRNKC/DigitalPhysics.digit-router-dataset
digit-router-dataset
34 709 Russian training rows for a two-step tool router over a catalogue of
95 headless utilities in 14 categories. Generated deterministically from the
catalogue's JSON schemas — no teacher model was used. 23.8 % of the rows are
refusals, and that fraction is the point of the dataset.
This is the set the published digitable-lol/digit-router-0.6b and
digitable-lol/digit-router-1.7b adapters were trained on.
1. Read this first: what this dataset… See the full description on the dataset page: https://huggingface.co/datasets/digitable-lol/digit-router-dataset.3-digit-arithmetic-scratchpad-traces
Contents
Split
Rows
train
100,000
validation
4,000
test
4,000
total
108,000
Splits are prompt-disjoint — no expression appears in more than one split,
and commutative swaps and trace keys are de-duplicated across splits to prevent
split leakage.
Operation
Rows
×
32,000
÷
32,000
+
22,000
−
22,000
Operands lie in [−999, 999]. Division answers use a fixed DDD.ddd form
(round-half-up to three decimals); division by zero is an atomic <nan>.… See the full description on the dataset page: https://huggingface.co/datasets/vmal/3-digit-arithmetic-scratchpad-traces.digit-eval-tasks
digit-eval-tasks
400 Russian evaluation tasks — 250 main, 150 red-team — for a system that is
required to answer only from a deterministic tool, a verbatim corpus quote, or a formal
certificate, and to refuse otherwise.
⚠️ Read this before you use it as a benchmark
This set was used while developing the gates it measures. It is no longer an
independent measuring stick.
On this set the system reports 1.0 % false answers (4/400). On a genuinely
independent held-out… See the full description on the dataset page: https://huggingface.co/datasets/digitable-lol/digit-eval-tasks.ultra-feedback-js-instruct
Ultra Feedback JS Instruct
A subset of the wonderful and elegant Ultra Feedback dataset. Ratings are 1-5 ( inclusive )
Generation Notebook
Example
{
"inst": "Refine the subsequent JavaScript code snippet to obtain the cumulative total of elements within an array:\nlet numbers = [1, 2, 3]",
"author": "codellama-34b-instruct",
"fun": "let numbers = [1, 2, 3];\nlet total = numbers.reduce((a, b) => a + b);\nconsole.log(total); // Output: 6",
"rating": "5"
}
digital-bg
Digital.bg articles
pii-masking-digital-pdi-200k
👉 Looking for the newest release? The current flagship is ai4privacy/pii-masking-openpii-1.5m. 1.6M samples, 30 languages, 19 PII classes, Asia Pacific extension.?** The current flagship is ai4privacy/pii-masking-openpii-1m. 1.4M samples, 23 languages, 19 PII classes.
🇪🇺 Personal Digital Information — European PII Dataset
Part of PII-Masking-2M (2,717,080 entries) by AI4Privacy
Entries
PII Annotations
Labels
Languages
Regions
198,319
815,110
33
23
29… See the full description on the dataset page: https://huggingface.co/datasets/ai4privacy/pii-masking-digital-pdi-200k.digits
digits
digits is a code dataset consisting of 900 public domain-like repos on GitHub.
The following languages included are:
C
C++
JavaScript
Python
R
PowerShell
Java
Kotlin
C#
Swift
Bourne Shell
This dataset is provided without warranty.