datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Python-Code-Solutions
Python Code Solutions
Features
1000k of Python Code Solutions for Text Generation and Question Answering
Python Coding Problems labelled by topic and difficulty
Recommendations
Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models.
Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic}
italic-softkd-pool
italic-softkd-pool
The exact training data of idealab-cs2/zagreus-0.4B-italic-softkd: 21,606 Italian multiple-choice questions with committee soft labels. One soft-KD training run from mii-llm/zagreus-0.4B-ita on the train split reaches 0.4787 on the full ITALIC 10K (official harness, 5-shot fast, temperature 0), from a 0.2802 base.
train is the full pool; the other three splits partition it by provenance:
split
rows
contents
train
21,606
the full training file (union… See the full description on the dataset page: https://huggingface.co/datasets/idealab-cs2/italic-softkd-pool.us-k12-schools-directory
US K-12 Schools Directory
A directory of 124,613 US K-12 schools covering all 50 states, DC, and US territories,
compiled from federal and state government sources. Each record carries directory
information (address, phone, website), enrollment and demographics, and, where a source
supplied it, a principal name and email.
This is a compilation of public government data. It is not a survey, and no field was
independently verified against the school itself.
Loading… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/us-k12-schools-directory.k12-standards-instruction-tasks
K-12 Curriculum Tasks (generated)
2,489 generated instruction/input/output records covering five curriculum tasks:
assessment creation, learning objective generation, misconception detection, standard
explanation, and standards Q&A. Content is predominantly mathematics.
Important: the name is misleading
Despite the name, this dataset contains no school directory data. There are four
columns - task, input, output, metadata - and no staff, principal, or school… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-standards-instruction-tasks.mantinc-catalan-drift
Mantinc — Catalan Drift Benchmark
Descripció (ca)
Mantinc és un banc de proves que avalua si un model de llenguatge continua
responent en català quan el missatge, la conversa prèvia o el context recuperat
l'empenyen a fer-ho en una altra llengua, normalment el castellà o l'anglès.
Dataset Description
Mantinc is a benchmark that measures whether a language model keeps answering
in Catalan when the prompt, prior conversation, or retrieved context… See the full description on the dataset page: https://huggingface.co/datasets/softcatala/mantinc-catalan-drift.jeopardy-clues
Jeopardy! Clues
568,068 Jeopardy! clues with their answers, categories, dollar values, air dates, and
round information, compiled from publicly archived, community-maintained transcriptions
of aired episodes.
Loading
from datasets import load_dataset
ds = load_dataset("robworks-software/jeopardy-clues")
science = ds["train"].filter(lambda x: x["category"] == "SCIENCE")
Splits
Split
Rows
train
482,857
validation
42,605
test
42,606… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/jeopardy-clues.nemotron-terminal-software_engineering
nemotron-terminal-software_engineering
Per-source partition of nvidia/Nemotron-Terminal-Corpus,
filtered to source == "software_engineering". The difficulty column preserves the original
easy / medium / mixed split (na for the dataset_adapters/* files, which
did not carry a difficulty label).
Partitioning scheme:
adapters_{code,math,swe} — rows from dataset_adapters/{code,math,swe}.parquet
{skill} (e.g. debugging, security, …) — rows from
synthetic_tasks/skill_based/{easy,medium… See the full description on the dataset page: https://huggingface.co/datasets/laion/nemotron-terminal-software_engineering.cosimo-cfa-frm-71k
Cosimo: Synthetic CFA/FRM Financial Reasoning Dataset
Cosimo is a synthetic, code-verified financial-exam question dataset for
training reasoning models and preference-tuned (DPO/ORPO) models. It contains
71,000 original, numerically-grounded questions spanning the CFA Level I–III
and FRM Part 1/2 curricula, each with a step-by-step chain-of-thought reasoning
trace.
Every numerical answer is computed by reference code, never sampled from a
language model. Reasoning traces are… See the full description on the dataset page: https://huggingface.co/datasets/btech-software/cosimo-cfa-frm-71k.optimot-linguistic-data
Optimot Linguistic Data
This dataset contains 4,011 entries extracted from the public Optimot linguistic consultation service of the Departament de Política Lingüística, Generalitat de Catalunya.
Each record addresses a Catalan language question or linguistic topic and includes an explanation, source metadata, and a direct source URL when available.
Data
The dataset is provided as JSON Lines:
optimot.jsonl
Each row contains:
Fitxa: Optimot card identifier.… See the full description on the dataset page: https://huggingface.co/datasets/softcatala/optimot-linguistic-data.k12-mathematics-standards-expanded
K-12 Mathematics Standards, expanded (generated instruction data)
4,965 instruction/input/output records for mathematics, generated around a K-12
standards taxonomy for instruction-tuning and educational-content experiments.
How this was built (read this first)
These are programmatically generated training examples, not curriculum written by
educators and not the text of any official standard. A generator combined standards
metadata - codes, grade levels, domains… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-mathematics-standards-expanded.k12-science-standards
[!WARNING]
Deprecated - use k12-science-standards-expanded instead.
This dataset is superseded: every instruction in this set also appears there, plus 1,123 more and nine additional metadata columns. Nothing here is unique to it.
It stays online so existing references keep resolving, but it will not be updated.
New work should point at robworks-software/k12-science-standards-expanded.
K-12 Science Standards (generated instruction data)
6,787 instruction/input/output records… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-science-standards.gbag-bench
GBAG-Bench — Grounded BI Answer Generation
A public benchmark for the step after the SQL: how faithfully an LLM interprets a query result into a natural-language answer.
NL2SQL measures half the problem. GBAG measures the other half.
📂 GitHub (harness, judge, leaderboard): softisight/gbag-bench
📊 Live leaderboard: LEADERBOARD.md
📐 Metric & rubric: METRIC.md
🪪 License: MIT (questions & harness) — bundled SQLite samples retain their original licenses
Why this… See the full description on the dataset page: https://huggingface.co/datasets/softisight-ai/gbag-bench.historical-training-manuals
Historical Training Manuals
1,597 US government and government-adjacent training manuals and technical publications
sourced from the Internet Archive, spanning roughly 1800-2021. Records carry
bibliographic metadata; a subset also carries extracted full text and a machine-generated
summary.
Loading
from datasets import load_dataset
ds = load_dataset("robworks-software/historical-training-manuals")
Splits
Split
Rows
train
1,277… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/historical-training-manuals.k12-ela-standards-expanded
K-12 ELA Standards, expanded (generated instruction data)
12,282 instruction/input/output records for English Language Arts, generated around a K-12
standards taxonomy for instruction-tuning and educational-content experiments.
How this was built (read this first)
These are programmatically generated training examples, not curriculum written by
educators and not the text of any official standard. A generator combined standards
metadata - codes, grade levels… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-ela-standards-expanded.k12-special-education-accommodations
K-12 Special Education Accommodations
A small reference dataset of special education accommodations and the federal IDEA
disability taxonomy. This is a reference table, not a corpus - 50 accommodation
records plus two small lookup tables.
Loading
from datasets import load_dataset
ds = load_dataset("robworks-software/k12-special-education-accommodations")
Contents
Table
Rows
Contents
train / validation / test
40 / 5 / 5
accommodation… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-special-education-accommodations.k12-mathematics-standards-aligned
[!WARNING]
Deprecated - use k12-mathematics-standards-expanded instead.
This dataset is superseded: every input in this set also appears there, plus 366 more and two additional metadata columns. Nothing here is unique to it.
It stays online so existing references keep resolving, but it will not be updated.
New work should point at robworks-software/k12-mathematics-standards-expanded.
K-12 Mathematics Standards (generated instruction data)
4,397 instruction/input/output records… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-mathematics-standards-aligned.ccisd-teks-enhanced
CCISD TEKS Enhanced (LLM-generated)
4,224 records built from the same 428 TEKS expectations as
ccisd-teks-training,
with additional LLM-written fields: detailed explanations, real-world applications,
prerequisite knowledge, common misconceptions, teaching strategies, assessment examples,
cross-curricular connections, and learning progressions.
The added content is LLM output and was not reviewed
The enrichment fields were generated by a language model. No educator… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/ccisd-teks-enhanced.k12-social-studies-standards
K-12 Social Studies Standards (generated instruction data)
15,982 instruction/input/output records for social studies (civics, history, geography, economics), generated around a K-12
standards taxonomy for instruction-tuning and educational-content experiments.
How this was built (read this first)
These are programmatically generated training examples, not curriculum written by
educators and not the text of any official standard. A generator combined standards… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-social-studies-standards.ccisd-teks-training
[!WARNING]
Deprecated - use ccisd-teks-enhanced instead.
This dataset is superseded: both cover the same 3,628 inputs, but that one carries eight further columns (teaching strategies, misconceptions, assessment examples and more). Nothing here is unique to it.
It stays online so existing references keep resolving, but it will not be updated.
New work should point at robworks-software/ccisd-teks-enhanced.
CCISD TEKS Training Set (generated)
4,224 instruction-tuning examples… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/ccisd-teks-training.k12-ela-standards
[!WARNING]
Deprecated - use k12-ela-standards-expanded instead.
This dataset is superseded: every input in this set also appears there, plus 1,433 more and five additional metadata columns. Nothing here is unique to it.
It stays online so existing references keep resolving, but it will not be updated.
New work should point at robworks-software/k12-ela-standards-expanded.
K-12 ELA Standards (generated instruction data)
6,487 instruction/input/output records for English Language… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-ela-standards.CPP-Code-Solutions
C++ Code Solutions
Features
1000k of Python Code Solutions for Text Generation and Question Answering
C++ Coding Problems labelled by topic and difficulty
Recommendations
Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models.
Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic}
ccisd-teks-alignment-split
[!WARNING]
Deprecated - use ccisd-teks-alignment instead.
This dataset is superseded: the two contain the same 428 rows with the same 12 columns; this copy only adds a train/validation/test partition, which you can reproduce in one line. Nothing here is unique to it.
It stays online so existing references keep resolving, but it will not be updated.
New work should point at robworks-software/ccisd-teks-alignment.
CCISD TEKS Alignment (pre-split)
The same 428 TEKS-to-course… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/ccisd-teks-alignment-split.jaquad-sft
softjapan/jaquad-sft
データセットの概要
このデータセットは、JaQuAD（Japanese Question Answering Dataset）をSFT（Supervised Fine-Tuning）形式に変換したものです。日本語の質問応答タスクに特化したinstruction tuning用のデータセットです。
データセットの詳細
言語: 日本語
タスク: 質問応答、instruction tuning
形式: SFT（instruction/input/output）
訓練データ: 31,748件
検証データ: 3,939件
合計: 35,687件
データ形式
各サンプルは以下の形式で構成されています：
{
"id": "tr-000-00-000",
"instruction": "次の文脈に基づいて質問に答えてください。可能なら短く正確に答えてください。",
"input":… See the full description on the dataset page: https://huggingface.co/datasets/softjapan/jaquad-sft.JS-Code-Solutions
Python Code Solutions
Features
1000k of JS Code Solutions for Text Generation and Question Answering
JS Coding Problems labelled by topic and difficulty
Recommendations
Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models.
Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic}
k12-science-standards-expanded
K-12 Science Standards, expanded (generated instruction data)
15,354 instruction/input/output records for science, generated around a K-12
standards taxonomy for instruction-tuning and educational-content experiments.
How this was built (read this first)
These are programmatically generated training examples, not curriculum written by
educators and not the text of any official standard. A generator combined standards
metadata - codes, grade levels, domains… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-science-standards-expanded.california-k12-standards
California K-12 Educational Standards
3,410 records organized around California K-12 standards frameworks, including Common
Core, NGSS, ELD, CTE, and Ethnic Studies. Records carry a standard identifier, grade
level, subject area, domain, and generated learning-objective and application text.
How this was built (read this first)
These records are programmatically generated, not transcribed from official standards
documents. A generator took a standards taxonomy -… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/california-k12-standards.Soft-CoT-1K
💡 The Idea
Good answers usually come from good thinking.
Soft-CoT-1K teaches models to reason before they respond using a lightweight, easy-to-train conversational format.
Instead of hiding the reasoning process, every sample explicitly contains it inside a <thinking> block before the final answer.
No complex templates.
No giant prompt engineering.
No unnecessary metadata.
Just:
Question
↓
Reason
↓
Answer
Simple enough for small models.
Useful enough for… See the full description on the dataset page: https://huggingface.co/datasets/WhirlwindAI/Soft-CoT-1K.multi-turn_dataset
Multi-turn Prompts Dataset
Description
This dataset consists of 400 text-only fine-tuned versions of multi-turn conversations in the English language based on 10 categories and 19 use cases. It has been generated with ethically sourced human-in-the-loop data methods and aligned with supervised fine-tuning, direct preference optimization, and reinforcement learning through human feedback.
The human-annotated data is focused on data quality and precision to enhance the… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/multi-turn_dataset.sft-conversational_datasetQuestion – Answer DatasetThe dataset contains 400 queries from two domains: Current Affairs and Creative Writing. It serves as a versatile resource for Natural Language Processing (NLP) tasks, including text classification, information retrieval, and model training.
Data attributes:
Query: The user-generated question. Data type: string.
Answer: The response provided by a team of writers and editors in markdown format, containing information related to the query.
Citations: Up to 4 credible… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/sft-conversational_dataset.simple-complex-singleturn-dataset
Simple/Complex Single-turn Prompts Dataset
Description
The dataset consists of 600 text-only prompts, each representing a fine-tuned instance of a single-turn user exchange in English. The samples are categorized into 10 distinct classes and cover 19 specific use cases. The dataset has been generated using ethically sourced human-in-the-loop data generation methods involving detailed insights of subject matter experts on labeled data for supervised fine-tuning to map… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/simple-complex-singleturn-dataset.