datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IFEval
Dataset Card for IFEval
Dataset Summary
This dataset contains the prompts used in the Instruction-Following Eval (IFEval) benchmark for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run:
from datasets import load_dataset
ifeval = load_dataset("google/IFEval")
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/IFEval.msi-corpus
Main Street Independent Corpus
The complete Main Street Independent archive as open data: 917 news articles and 0 opinion columns, each with full text and metadata. AI-generated news and opinion, dedicated to the public domain under CC0 — no rights reserved. Refreshed daily.
Load it
from datasets import load_dataset
ds = load_dataset("golfplan18/msi-corpus") # 'news' and 'opinion' splits
print(ds["news"][0]["headline"], ds["news"][0]["text"][:200])… See the full description on the dataset page: https://huggingface.co/datasets/golfplan18/msi-corpus.gspc-gov
GSPC — governance bank (GovBench)
Bank (governance). Frozen split. Live n is the governance row on GET https://councilof.ai/api/gspc, not a Hub leaderboard score. Not a certificate.
Art 50 dates (EUR-Lex): 2 August 2026 live; marking grace 2 December 2026.
Council of AI measurement bank. Measurement, not certification.
Live measurement. This bank stands behind the governance row of the live GSPC board: GET https://councilof.ai/api/gspc?axis=governance (family, kind, status and… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-gov.gspc-jail-goldbank
GSPC — jail bank (GoldBank-Detector)
Council of AI measurement bank. Measurement, not certification.
Bank. Frozen split. Live n is the matching axis on GET https://councilof.ai/api/gspc, not a Hub score. Not a certificate. Art 50 (EUR-Lex): 2 August 2026 live; marking grace 2 December 2026.
Live measurement. This bank stands behind the jail row of the live GSPC board: GET https://councilof.ai/api/gspc?axis=jail (family, kind, status and n are on that row, never typed here; the… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-jail-goldbank.MathOlympiadBenchThis repository contains the MathOlympiadBench dataset, which is introduced in the paper Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction.
Project Page: https://blog.goedel-prover.com
Code Repository: https://github.com/Goedel-LM/Goedel-Prover-V2
MathOlympiadBench (Math Olympiad) comprises human-verified formalizations of Olympiad-level mathematical competition problems, sourced from Compfiles and IMOSLLean4 repository. MathOlympiadBench… See the full description on the dataset page: https://huggingface.co/datasets/Goedel-LM/MathOlympiadBench.go-swe-bench-v0
go_swe_bench v0 — real Go bug fixes, verified by the Go toolchain
246 tasks from 79 real Go repositories. Each task is a bug-fix commit whose co-committed test is red on the
parent and green on the fix. No LLM anywhere in the build.
Mined on 2026-09-19 from the GuildLM Go mining pipeline by inverting the filter that had thrown the tests
away (the pipeline was built for SFT data; a benchmark needs the opposite). Every task was verified twice
with go test: green at the commit (≥ 1… See the full description on the dataset page: https://huggingface.co/datasets/guildlm/go-swe-bench-v0.sn38-quality-gold-100k
SN38 quality prompt + gold continuation
Synthetic incomplete-sentence prompts with gold continuations for Bittensor
subnet 38. 13 categories, 13 items per category per call,
temperature 1.0.
Each row:
category: reading_comprehension, language_understanding, world_knowledge, commonsense_reasoning, language_modeling, causal_reasoning, logical_inference, temporal_reasoning, math_reasoning, truthfulness, pronoun_resolution, paraphrase_detection, word_sense_disambiguation
prompt:… See the full description on the dataset page: https://huggingface.co/datasets/jjjlimaus/sn38-quality-gold-100k.Function_Calling_Private_GG
Function Recommendation Dataset Readme
Description
This dataset is based on the "glaiveai/glaive-function-calling" repository and has been customized to suit my specific requirements. It is designed for fine-tuning a Large Language Model (LLM) on the task of generating function recommendations in a conversational context. The dataset contains 158,738 snippets of conversations between me and my virtual assistant named J.O.S.I.E. (Just an Outstandingly Smart Intelligent… See the full description on the dataset page: https://huggingface.co/datasets/Goekdeniz-Guelmez/Function_Calling_Private_GG.Go-Code-Large
Go-Code-Large
Go-Code-Large is a large-scale corpus of Go (Golang) programming language source code, comprising 316,427 code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, cloud-native systems, and modern backend software engineering.
By offering a focused and curated dataset for Go, this corpus enables experimentation in concurrent programming, distributed systems, and… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Go-Code-Large.Persian-Business-Text-to-SQL-Gold-1K
Persian Business Text-to-SQL Gold-1K
1,000 Persian-native, execution-verified business Text-to-SQL examples for fine-tuning and benchmarking.
مجموعهای ۱۰۰۰ نمونهای برای تبدیل درخواستهای فارسی کسبوکار به SQL، همراه با دیتابیسهای SQLite اجرایی، schema کامل، متادیتای سختی/مهارت و ارزیابی مبتنی بر Execution Accuracy.
Motivation
BIRD emphasizes database-grounded Text-to-SQL and execution accuracy; Spider 2.0 pushes toward realistic enterprise database workflows.… See the full description on the dataset page: https://huggingface.co/datasets/jumplander/Persian-Business-Text-to-SQL-Gold-1K.VeriLoop-Governed-Recurrence-Verified
VLR-Recurrence-Verified
VLR-Recurrence-Verified is a synthetic-data construction release for studying
evidence-convergent program repair. It operationalizes a protected partial order:
a candidate is positive only when it preserves every already-satisfied
obligation and strictly improves at least one unresolved obligation.
Scale
Split
Tasks
Families
Transitions
Balanced pairs
Certified finals
Train
3,500
28
12,250
49,000
3,500
Validation
750
10
2,623… See the full description on the dataset page: https://huggingface.co/datasets/tsinghua-sigs-robot-lab/VeriLoop-Governed-Recurrence-Verified.wikipedia-human-ai
Wikipedia Human/AI
A selection of ~10,000 paragraphs from Wikipedia, along with rewritten text by GPT 5 Nano.
golang-coderQ&A style combined, deduplicated dataset including portions of:
Golang best practices and coding guides (general Q&A) https://huggingface.co/datasets/smcleod/golang-programming-style-best-practices (MIT)
Golang questions (general Q&A) https://huggingface.co/datasets/ExAi/Code-Golang-QA-2k (Apache2)
Golang functions (code & description) https://huggingface.co/datasets/google/code_x_glue_ct_code_to_text (c-uda)
Golang snippets (code & description)… See the full description on the dataset page: https://huggingface.co/datasets/smcleod/golang-coder.sud-resh-benchmark
Представляем вашему вниманию бенчмарк для оценки ответов больших языковых моделей в домене российского права.
Бенчмарк создан на вычислительный грант от Yandex OpenSource
Бенчмарк основан на анонимизированных решениях судов в следующих отраслях:
Административное право
Конституционное право
Экологическое право
Финансовое право
Гражданское право
Семейное право
Право социального обеспечения
Трудовое право
Уголовное право
Жилищное право… See the full description on the dataset page: https://huggingface.co/datasets/lawful-good-project/sud-resh-benchmark.Expert-Go-SFT-100K
Expert-Go-SFT-100K
Paper | Code
Expert-Go-SFT-100K is a large-scale synthetic dataset designed to "cold start" Large Language Models (LLMs) for Go-related reasoning tasks. It was introduced as part of the LoGos project, which aims to bridge the gap between general-purpose LLM reasoning and specialized expert knowledge in the game of Go.
The dataset features 100,000 samples of structured Go expertise mixed with general long Chain-of-Thought (CoT) reasoning data. It enables models to… See the full description on the dataset page: https://huggingface.co/datasets/YichuanMa/Expert-Go-SFT-100K.dsg-state-continuation
DSG State-Continuation
Training data for graph-conditioned long-form fiction generation: given the
narrative state a reader would hold after chapters 1..t-1, and a one-line brief
for chapter t, write chapter t.
Built from 215 public-domain novels (Project Gutenberg, English fiction),
segmented into chapters. 6,876 examples.
Why the state is built this way
The state is not a summary and not a retrieval index. It is a revision-aware
assertion store built causally —… See the full description on the dataset page: https://huggingface.co/datasets/GOVINDFROM/dsg-state-continuation.gold-trace-cyber-defense-50
Gold Trace Cyber Defense 50
This is a 50-row public sample from a frozen 750-instance Cyber Defense release family: 500 public-development instances plus a source-family-disjoint 250-instance private evaluation set.
Only rows from the frozen 500-instance public-development pack are included here. The separate 250-instance private evaluation set, its rows, answers, and source contents are not included.
Sample composition
10 public scenario families.
5 rows per… See the full description on the dataset page: https://huggingface.co/datasets/novcor/gold-trace-cyber-defense-50.gorilla-16k
Training Dataset for Gorilla
Gorilla's self instruct training datasets for huggingface, torchhub, and tensorflowhub apis.
Source: https://gorilla.cs.berkeley.edu/
2026-08-17-table2-9284-peer-critique-good-716-train-mixture
Qwen3.6-27B SFT mixture: 9,284 Table2 + 716 peer_critique GOOD ARM (10,000 rows)
The one-variable twin of LASR-Callum/2026-08-16-table2-9284-peer-critique-716-train, whose
716 peer-critique rows are 358 good / 358 flawed. Here all 716 are drawn from the good arm.
field
value
experiment
Arm ablation: does the peer-critique FLAWED arm contribute anything? Train on good-arm-only critiques and compare against the 358/358 arm.
date_generated
2026-08-17
constitution… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-08-17-table2-9284-peer-critique-good-716-train-mixture.Python_GOD_Coder_Omniforge_AI_12k
Python GOD Coder Omniforge AI 12k
Creator: Within Us AI
A 12,000-row mixed-format Python coding dataset designed as a sharpening corpus for building a small but dangerous Python specialist.
This dataset is intentionally focused on the practical behaviors that matter for a modern Python coding model:
implementation with tests
strict code-only instruction following
debugging and repair
refactoring for readability and production readiness
next-token code completion… See the full description on the dataset page: https://huggingface.co/datasets/WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k.gomodel-go-expert-v4
GoModel Go Expert v4 Dataset
Description
A high-quality dataset for fine-tuning Qwen2.5-Coder-7B to be an expert Go software engineer
with tool-calling capabilities. This is version 4, substantially rebuilt from v3 with:
Structured messages format (not pre-rendered ChatML text)
Go AST-extracted code from real repositories using go/parser
Go 1.26 feature coverage (February 2026 release)
Senior/staff-level engineering content (architecture, distributed systems, API… See the full description on the dataset page: https://huggingface.co/datasets/mencosk/gomodel-go-expert-v4.gopus-1xs
🧠 Gopus-1XS Dataset
Gopus-1XS est un dataset multilingue de haute qualité contenant des paires instruction-réponse pour l'entraînement de modèles de langage conversationnels.
📊 Statistiques du Dataset
Métrique
Valeur
Échantillons totaux
460
Langues
Français (majoritaire), Anglais
Catégories
6+
Longueur moyenne
250 tokens
Format
JSONL
🏷️ Structure des Données
Chaque échantillon contient les champs suivants :
{
"instruction":… See the full description on the dataset page: https://huggingface.co/datasets/Gopu-poss/gopus-1xs.storyweaver-writing-zh
StoryWeaver 中文写作质量评测集
12 道按写作失效模式反推设计的中文创作题、4 个参赛者写出的 48 篇章节、432 条逐维度两两判决（含裁判完整推理原文）。
来自 StoryWeaver 的写作质量评测轨道。榜单：https://storyweaver.cn/benchmark-writing.html
核心结论
接系统比换一代底模更管用。同一底模接上多 Agent 系统后的胜率：k2.5 **75.1%**、k2.6 **60.2%**；而 k2.5(系统) 对 k2.6(裸) 是 70.3%，反过来只有 37.2%——系统加持能把旧一代底模抬过裸的新一代底模。系统档拿下 22 个维度里的 20 个榜首，包括全部 9 个负向维度。
k2.5 与 k2.6 之间 54.7%，落在噪音带内，不构成结论。
题目怎么设计的
每道题咬住 rubric 里的一个维度或负向维度，用硬约束逼出功力：… See the full description on the dataset page: https://huggingface.co/datasets/godwei123/storyweaver-writing-zh.taboo-gold
taboo-gold
This dataset contains conversational data in JSONL format, suitable for Supervised Fine-Tuning (SFT).
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("bcywinski/taboo-gold")
Format
The dataset is in JSONL format where each line contains a conversation record suitable for training chat models.
gohumanize-open-humanizer-dataset
GoHumanize Open Humanizer Dataset
2,957 training pairs and 300 test pairs for teaching a language model to rewrite
AI-styled English prose into natural human writing. Each pair is:
input: a passage rewritten by a large language model in the register typical of LLM output
(formal, smooth, hedged, connective phrases, no contractions);
output: the original human-written passage, from a public-domain book or, since version 2,
from a US federal government publication.
The human… See the full description on the dataset page: https://huggingface.co/datasets/gohumanize/gohumanize-open-humanizer-dataset.Go-GRPO-1K
Go-GRPO-1K
Paper | Code
Project Context
The LoGos model uses this dataset to transfer reasoning capabilities acquired from long CoT data to Go tasks. Through mixed fine-tuning and reinforcement learning, the model learns to perform analysis, reasoning, and summarization to select optimal moves on the Go board.
Citation
If you find this dataset useful for your research, please cite:
@misc{ma2026mixingexpertknowledgebring,
title={Mixing Expert Knowledge:… See the full description on the dataset page: https://huggingface.co/datasets/YichuanMa/Go-GRPO-1K.gordon-ramsay-code-review-v2
Gordon Ramsay Code Review & Auditor Corpus v2 (dcmutlu/gordon-ramsay-code-review-v2)
A high-density synthetic dataset of 10,000 multi-turn code review pairs designed to fine-tune open-weight reasoners (specifically Qwen2.5-Coder-7B-Instruct) into Chef Gordon Ramsay: Sovereign Executive Code Auditor and Supreme Software Gastronomer.
🍳 Dataset Overview
This dataset merges rigorous computer science diagnostics (Abstract Syntax Tree inspection, concurrency lifecycle… See the full description on the dataset page: https://huggingface.co/datasets/dcmutlu/gordon-ramsay-code-review-v2.goldensets
LEGEX Goldensets: Expert-Coded Review-Table Annotations
This repository contains the expert-coded gold annotations for the LEGEX
benchmark of civil-judgment review-table extraction. 1,548 judgments across
19 jurisdictions have been annotated by hand against a shared 14-field schema
covering monetary outcomes, cost allocation, party structure, and industry
classification. Including independent secondary re-annotations, the release
holds 1,974 annotation rows.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/legexbenchmark/goldensets.llm-jp-corpus-v4-ja_e-gov
llm-jp-corpus-v4 — ja_e-gov
Mirror of the ja/ja_e-gov sub-corpus of LLM-jp Corpus v4,
built by the LLM-jp Corpus Building WG (NII).
Source: https://gitlab.llm-jp.nii.ac.jp/datasets/llm-jp-corpus-v4
Sub-corpus: ja_e-gov
Files: 2 × jsonl.gz (0.1 GB compressed)
Format: one JSON object per line, with a text key and a meta key
(document id, URL, and other provenance fields).
Directory layout mirrors the upstream repository.
License
CC BY 4.0 — inherited from the… See the full description on the dataset page: https://huggingface.co/datasets/Podtech/llm-jp-corpus-v4-ja_e-gov.goal-pashto-chat-sharegpt-5GB
📄 goal-pashto-chat-sharegpt-5GB — Pashto ShareGPT‑Style Chat Dataset
A large‑scale, high‑quality Pashto conversational dataset designed for instruction‑tuning, dialogue modeling, and LLM alignment.This dataset contains ~5GB of multi‑turn Pashto conversations inspired by ShareGPT, covering reasoning, advice, education, culture, and general knowledge.
📌 Dataset Summary
goal-pashto-chat-sharegpt-5GB is a curated collection of Pashto user–assistant conversations… See the full description on the dataset page: https://huggingface.co/datasets/nassimjp/goal-pashto-chat-sharegpt-5GB.