datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ChatGPT-4o-Writing-Prompts
ChatGPT-4o Writing Prompts
This is a dataset containing 3746 short stories, generated with OpenAI's chatgpt-4o-latest model and using Reddit's Writing Prompts subreddit as a source. Each sample is generally between 6000-8000 characters long.
These stories were thoroughly cleaned and then further enriched with a title and a series of applicable genres.
Note that I did not touch the Markdown ChatGPT-4o produced by itself to enrich its output, as I very much enjoy the added flavour… See the full description on the dataset page: https://huggingface.co/datasets/Gryphe/ChatGPT-4o-Writing-Prompts.japan-math-philosophy-prompts
Japan Math Philosophy Prompts
Microdataset autoral com problemas que combinam matemática e reflexão
filosófica. Há 24 registros: oito instâncias editoriais, cada uma localizada em
pt-BR, en e ja e mantida integralmente no split train.
Todo o conteúdo foi gerado por modelo e permanece sem revisão humana. As
respostas matemáticas funcionam como gabaritos curtos; os critérios filosóficos
indicam qualidades esperadas de uma justificativa, não uma opinião obrigatória.… See the full description on the dataset page: https://huggingface.co/datasets/guicybercode/japan-math-philosophy-prompts.allenai-WildChat-4.8M-prompts
allenai/WildChat-4.8M English Prompts
Dataset Summary
This dataset contains real user-submitted prompts to ChatGPT, extracted from the English portion of the allenai/WildChat-4.8M collection.
It serves as a large-scale resource for analyzing user intent, conversational diversity, and prompt engineering patterns.
Files
en_prompts: All English-language first messages from user conversations.
Each record represents the first user prompt.
Exact duplicates are… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/allenai-WildChat-4.8M-prompts.turkish-flow-drafter-prompts
Turkish prompts for Chained-Flow drafter training
Chat-templated Turkish prompts used to train and evaluate the Turkish
Flow-Drafter
checkpoints for Qwen/Qwen3.5-4B / 9B / 27B.
Prompts only — no completions. A drafter is trained on the target model's own hidden states, so
continuations are generated locally by running the target over these prompts. Nothing here is a
model output.
split
rows
what it is
v1/
29,100 train + 300 holdout
the mixture the released Turkish… See the full description on the dataset page: https://huggingface.co/datasets/selimaktas/turkish-flow-drafter-prompts.turkish-flow-drafter-prompts
GitHub repo ·
Technical blog ·
Model collection
Turkish prompts for Chained-Flow drafter training
Chat-templated Turkish prompts used to train and evaluate the Turkish
Flow-Drafter
checkpoints for Qwen/Qwen3.5-4B / 9B / 27B.
Prompts only — no completions. A drafter is trained on the target model's own hidden states, so
continuations are generated locally by running the target over these prompts. Nothing here is a
model output.
split
rows
what it is
v1/… See the full description on the dataset page: https://huggingface.co/datasets/ytu-ce-cosmos/turkish-flow-drafter-prompts.english-flow-drafter-prompts
English prompts for Chained-Flow drafter training
Chat-templated English prompts used to train the English
Flow-Drafter
checkpoints for Qwen/Qwen3.5-4B / 9B / 27B.
Prompts only — no completions. A drafter is trained on the target model's own hidden states, so
continuations are generated locally by running the target over these prompts. Nothing here is a
model output.
split
rows
prompt tokens
what it is
v1/
19,672 train + 500 holdout
1,518,620
the original mixture… See the full description on the dataset page: https://huggingface.co/datasets/selimaktas/english-flow-drafter-prompts.prompt-slimmer-slm
Prompt Slimmer SLM — Demo Dataset
Synthetic examples for experimenting with prompt rewriting and sentence selection. Exported without changing the examples or their original splits from the shared GitHub codebase.
Model · Project page
Configuration
Train
Validation
Test
Purpose
rewrites-expanded (default)
41
2
2
Expanded rewriting dataset: 45 examples
rewrites
9
2
2
Original dataset used by the first adapter
selector
256
64
64
KEEP/DROP labels for source spans… See the full description on the dataset page: https://huggingface.co/datasets/ai-mitra/prompt-slimmer-slm.english-flow-drafter-prompts
GitHub repo ·
Technical blog ·
Model collection
English prompts for Chained-Flow drafter training
Chat-templated English prompts used to train the English
Flow-Drafter
checkpoints for Qwen/Qwen3.5-4B / 9B / 27B.
Prompts only — no completions. A drafter is trained on the target model's own hidden states, so
continuations are generated locally by running the target over these prompts. Nothing here is a
model output.
split
rows
prompt tokens
what it is
v1/… See the full description on the dataset page: https://huggingface.co/datasets/ytu-ce-cosmos/english-flow-drafter-prompts.iceland-tech-christian-ethics-prompts
Fictional Icelandic Landscapes, Technology and Christian Ethics Prompts
This microdataset contains 24 original discussion prompts arranged as 12
parallel pt-BR/English pairs. Each explicitly fictional scenario combines a
landscape motif inspired by Iceland, a technology-governance dilemma, and
concepts that may be explored through Christian ethics. The records do not
describe real Icelandic institutions, policies, communities, or practices, and
they do not claim that Christians… See the full description on the dataset page: https://huggingface.co/datasets/guicybercode/iceland-tech-christian-ethics-prompts.internet-prompts-benchmark
Internet Prompts Benchmark
Viral internet prompts, memes, and tests that AI historically failed at. Popular ones like counting letters in the word strawberry and nicher ones that test other important capabilities.Mostly made by GPT-5.6 Sol.
It is designed for many types of models to participate, small and large, not only transformers.
It has prompts from the early days of AI to the very latest.
It will be actively updated to preserve various prompts for as long as I can afford… See the full description on the dataset page: https://huggingface.co/datasets/NikoThePig/internet-prompts-benchmark.diverse-svg-prompts
Diverse SVG Prompts
Diverse SVG Prompts is a public collection of 20,000 high-quality,
generated and filtered English briefs for SVG and vector-graphics generation.
It contains 18,000 general illustration prompts and 2,000 lettering prompts.
Schema
The dataset intentionally has only two columns:
prompt: the complete visual brief.
type_tags: a list of category, author-model, and processing tags.
Example:
{
"prompt": "A moonlit mechanical heron..."… See the full description on the dataset page: https://huggingface.co/datasets/Nbardy/diverse-svg-prompts.PromptSD
PromptSD
Training and evaluation data for PromptSD, an on-policy soft-prompt-teacher distillation method.
The release covers the four target tasks used in the paper. Every example carries a
<reasoning>...</reasoning> chain followed by a <answer>...</answer> span, so the data can be used
directly for reasoning-supervised SFT, distillation, or RLVR.
Configurations
Config (config_name)
Task
Source / format
Train
Validation
Test
science
Science MCQ
4-way… See the full description on the dataset page: https://huggingface.co/datasets/gray311/PromptSD.synthetic-instruction-prompts
Synthetic Instruction Prompts (8 domains)
Most synthetic prompt sets are a black box. You get a pile of prompts and no idea whether they're actually varied or just the same three sentences wearing different nouns. This one is graded, and the grade is on the card.
It's 2,829 instruction-style prompts across eight domains, generated with SynthKit and then scored by the same tool. The prompts carry no answers. Think of them as seed prompts: you feed them to a model to bootstrap… See the full description on the dataset page: https://huggingface.co/datasets/LaelaZorana/synthetic-instruction-prompts.promptlean-prompts
PromptLean Prompts
120 prompts across 14 categories, each in three variants: Lean, Balanced, and Max Quality. Averaged across the library, the Lean variant uses about 86% fewer tokens than Max Quality.
This is the data behind PromptLean.
The idea
Most published prompts are overengineered. A code review does not need 200 tokens of preamble, but some tasks genuinely do earn the extra context. Keeping all three variants side by side makes that tradeoff explicit and… See the full description on the dataset page: https://huggingface.co/datasets/kishormorol/promptlean-prompts.ministral-3-benchmark-prompts
Ministral 3 MLX benchmark prompts
This tiny dataset contains the four fixed prompts used by the reproducible
smoke benchmark for the Ministral 3 MLX 4-bit model.
It is a benchmark fixture, not a training or fine-tuning dataset.
Schema
Each JSONL row contains:
id: stable case identifier;
language: prompt language;
prompt: exact input sent to the model;
expected_keywords: lowercase substrings used by the smoke check.
The benchmark uses greedy decoding and checks… See the full description on the dataset page: https://huggingface.co/datasets/vinci00/ministral-3-benchmark-prompts.Manim-8600-Prompts
ManimCoder Prompts
An English prompt dataset for generating Manim Community scenes and related engineering tasks.
Dataset size
Source collection: 9,000 records
Deduplicated release: 8,600 prompts
Removed structural duplicates: 400
The removed records came from one source section where each of 100 primary 3D objectives had been repeated five times with only the camera or reveal instruction changed. One variant per primary objective was retained.… See the full description on the dataset page: https://huggingface.co/datasets/nmsofficial/Manim-8600-Prompts.alpaca-bulgarian-jokes-multilingual-prompts
Bulgarian Jokes Dataset
Overview
The Bulgarian Jokes Dataset is a collection of Bulgarian-language jokes gathered and prepared for use in training and fine-tuning natural language processing (NLP) models. This dataset is designed to help researchers and developers build models capable of understanding and generating humorous content in Bulgarian.
Dataset Structure
The dataset is structured in a format suitable for NLP training and fine-tuning tasks, such as the… See the full description on the dataset page: https://huggingface.co/datasets/vislupus/alpaca-bulgarian-jokes-multilingual-prompts.nepi-prompts-dataset
NEPI: Narrative-Embedded Prompt Injection Dataset (Sanitized)
Dataset Summary
This dataset contains 4,000 sanitized prompts designed for research on prompt injection vulnerabilities in Large Language Models (LLMs).It introduces and supports evaluation of a novel attack class called Narrative-Embedded Prompt Injection (NEPI), where adversarial intent is embedded inside coherent fictional narratives, dialogues, or persona-driven roleplay prompts.
Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/rupeshreddypapa/nepi-prompts-dataset.ml-swe-prompts
ML SWE Prompts
Unified collection of ML/training-related software engineering prompts for OPD distillation training. All prompts are in English.
Filtered to core ML repos: huggingface (1,058), numpy (937), Lightning-AI (377), ray-project (342). Excludes pandas-dev, qiskit, open-mmlab, scipy, tensorflow, spaCy.
Splits
Config
Source
Rows
Description
all
Combined
6,220
All prompts combined
swe_bench_ml
SWE-bench train
2,714
Problem statements from core ML repos… See the full description on the dataset page: https://huggingface.co/datasets/harithoppil/ml-swe-prompts.system_prompts_SuperGPQA-26000xSFT system prompts dataset generated using openai/gpt-oss-120b and m-a-p/SuperGPQA dataset.
Each instance follows this format:
{
"uuid": "000192f411a04f13858d69834a44ae01",
"messages": [
{
"role": "system",
"content": "You are a system prompt generator."},
{
"role": "user",
"content": "Write a system prompt that defines an AI researcher who is a leading authority in Science, specifically in Physics and Quantum Mechanics."
},
{
"role":… See the full description on the dataset page: https://huggingface.co/datasets/kth8/system_prompts_SuperGPQA-26000x.vidiary-reflective-prompts
ViDiary Reflective Prompts & Emotional Taxonomy Dataset
This open dataset contains foundational reflective journaling prompts and emotional sentiment taxonomy used in the development of ViDiary — the AI-powered voice and video journal with dual-PIN Decoy Vault.
🎙️ About ViDiary
ViDiary is an innovative mobile application engineered to solve the #1 psychological hurdle in personal self-care: Bedtime Typing Fatigue.
Research shows that over 80% of… See the full description on the dataset page: https://huggingface.co/datasets/YILMAZB1/vidiary-reflective-prompts.system_prompts_Jobs-20000xSFT system prompts dataset generated using openai/gpt-oss-120b and Faker jobs library.
Each instance follows this format:
{
"uuid": "7ef8e7a637934d1d9ddf0856ba6bda98",
"messages": [
{
"role": "system",
"content": "You are a system prompt generator."
},
{
"role": "user",
"content": "Design a system prompt for an AI assistant that excels at answering advanced questions about Outdoor activities/education manager."
},
{
"role": "assistant"… See the full description on the dataset page: https://huggingface.co/datasets/kth8/system_prompts_Jobs-20000x.llm-redteam-owasp-prompts
LLM Red-Team Prompts — OWASP LLM Top 10
A curated dataset of 150 adversarial red-team prompts for evaluating the
safety and robustness of large language models, mapped to the
OWASP LLM Top 10.
Every prompt is a real payload extracted directly from the open-source
llm-safety-auditor
project — none are fabricated.
The dataset combines two sources from that project:
50 hand-curated attack templates (attack_library) — 10 per attack category.
100 mutation-engine variants… See the full description on the dataset page: https://huggingface.co/datasets/9mark9/llm-redteam-owasp-prompts.xio-compliance-brain-triad-prompts
XIO Compliance Brain — Triad Reviewer Prompts
Reusable system prompts for running a multi-voice compliance debate against the same matter — the heart of XIO Compliance Brain's "Triad Review Engine" pattern.
This dataset extracts the production prompts from the open-source compliance-AI hackathon branch so others can replicate the Triad pattern (three reviewer voices + synthesis + optional Round 2) on any LLM that follows OpenAI-compatible chat APIs.
What's in this… See the full description on the dataset page: https://huggingface.co/datasets/slavazeph/xio-compliance-brain-triad-prompts.vcl-ai-coding-prompts
VCL AI Coding Power Prompts
50 battle-tested prompts for Claude Code, Codex, Gemini CLI, and Cursor — by Vibe Coder's Life.
Free catalog for vibe coders. Replace {{PLACEHOLDERS}} with your facts. Not the paid Apify Playbook prompt pack (those stay private).
Load
from datasets import load_dataset
ds = load_dataset("kondasviktor/vcl-ai-coding-prompts", "prompts")
print(ds["train"][0]["title"])
Columns
Column
Description
id
Stable id… See the full description on the dataset page: https://huggingface.co/datasets/kondasviktor/vcl-ai-coding-prompts.nepi-prompts-dataset
NEPI: Narrative-Embedded Prompt Injection Dataset (Sanitized)
Dataset Summary
This dataset contains 4,000 sanitized prompts designed for research on prompt injection vulnerabilities in Large Language Models (LLMs).It introduces and supports evaluation of a novel attack class called Narrative-Embedded Prompt Injection (NEPI), where adversarial intent is embedded inside coherent fictional narratives, dialogues, or persona-driven roleplay prompts.
Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/Vaibhav-GOAT/nepi-prompts-dataset.sarvam-30b-audit-prompts
Sarvam-30B Responsible-AI Audit — Pre-Registered Prompt Manifest
120 prompts across 5 categories, sampled deterministically (seed = 42) and pre-registered
as the eval contract for a public responsible-AI audit of
Sarvam-30B, India's sovereign-built
reasoning LLM.
This dataset is the eval contract committed to git before any prompt was sent to the model.
Reviewers can verify every prompt by going to the cited source and pulling that exact row.
Composition
#… See the full description on the dataset page: https://huggingface.co/datasets/procodec/sarvam-30b-audit-prompts.am-deepseek-r1-distilled-prompts-1.4m
AM DeepSeek R1 Distilled Prompts 1.4M
This dataset contains prompt-only rows extracted from a-m-team/AM-DeepSeek-R1-Distilled-1.4M.
Extraction
For each source JSONL row, every message with role == "user" was emitted as one prompt row. Assistant responses, reasoning traces, answers, and source metadata were not included.
Source files:
am_0.5M.jsonl.zst
am_0.9M.jsonl.zst
Extraction results:
Input rows: 1,400,000
Output prompt rows: 1,400,000
JSON parse errors: 0… See the full description on the dataset page: https://huggingface.co/datasets/tim-gabie/am-deepseek-r1-distilled-prompts-1.4m.llm-attacked-prompts-clm
LLM-Paraphrased Adversarial Prompts
LLM-paraphrased adversarial prompts for three code-generation benchmarks
(MBPP+, HumanEval+, CanItEdit), used by
RobustEval-CLM's
LLMParaphraseAttack.
Each row corresponds to one task in the source benchmark and carries the
original prompt alongside an adversarial rewrite produced by an LLM under a
BERTScore faithfulness constraint.
Configs
config
source benchmark
rewrite surface
mbpp
MBPP+
line 1 of the 4-line prompt… See the full description on the dataset page: https://huggingface.co/datasets/TheFatBlue/llm-attacked-prompts-clm.Gryphe_ChatGPT-4o-Writing-Prompts-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
Gryphe_ChatGPT-4o-Writing-Prompts-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
Gryphe/ChatGPT-4o-Writing-Prompts with responses regenerated with gemini-2.0-flash-thinking-exp-1219.
Generation Details
If BlockedPromptException, StopCandidateException, or InvalidArgument was returned, the sample was skipped.
If ["candidates"][0]["safety_ratings"] == "SAFETY" the sample was skipped.
If ["candidates"][0]["finish_reason"] != 1 the sample was skipped.
model =… See the full description on the dataset page: https://huggingface.co/datasets/PJMixers-Dev/Gryphe_ChatGPT-4o-Writing-Prompts-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT.