Dataset Card for Dataset Name

This datset is a collection of 100 system prompts for large language models.

  Dataset Details





  Dataset Description

These 100 system prompts test a model's ability to follow grammatical patterns; answer basic multiple choice questions; act according to a particular persona; memorize information; and speak in French. Files:

hundred_system_prompts.py: refer to this to see the (prompt, probe, function) triplets, as well as the… See the full description on the dataset page: https://huggingface.co/datasets/Naomibas/llm-system-prompts-benchmark.

Image generated by DALL-E. See prompt for more details

  📝🌐 Synthetic Multilingual LLM Prompts

Welcome to the "Synthetic Multilingual LLM Prompts" dataset! This comprehensive collection features 1,250 synthetic LLM prompts generated using Gretel Navigator, available in seven different languages. To ensure accuracy and diversity in prompts, and translation quality and consistency across the different languages, we employed Gretel Navigator both as a generation tool and as an… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/synthetic_multilingual_llm_prompts.

Dataset Card for "malicious-llm-prompts-v4"

More Information needed

beephids/paper-llm-prompts dataset hosted on Hugging Face and contributed by the HF Datasets community

🧠 Awesome ChatGPT Prompts [CSV dataset]

This is a Dataset Repository of Awesome ChatGPT Prompts View All Prompts on GitHub

  License

CC-0

kaiquedu/speedrender-llm-prompt dataset hosted on Hugging Face and contributed by the HF Datasets community

Official LLM System Prompts

This short dataset contains a few system prompts leaked from proprietary models. Contains date-stamped prompts from OpenAI, Anthropic, MS Copilot, GitHub Copilot, Grok, and Perplexity.

In-The-Wild Jailbreak Prompts on LLMs

This is the official repository for the ACM CCS 2024 paper "Do Anything Now'': Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models by Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang. In this project, employing our new framework JailbreakHub, we conduct the first measurement study on jailbreak prompts in the wild, with 15,140 prompts collected from December 2022 to December 2023 (including 1,405… See the full description on the dataset page: https://huggingface.co/datasets/TrustAIRLab/in-the-wild-jailbreak-prompts.

System Prompts Dataset - August 2025

Point-in-time export from Daniel Rosehill's system prompt library as of August 3rd, 2025

  Overview

This repository contains a comprehensive collection of 944 system prompts designed for various AI applications, agent workflows, and conversational AI systems. While many of these prompts now serve as the foundation for more complex agent-based workflows, they continue to provide essential building blocks for AI system design and… See the full description on the dataset page: https://huggingface.co/datasets/danielrosehill/System-Prompt-Library-030825.

hse-llm/prompt-injections dataset hosted on Hugging Face and contributed by the HF Datasets community

Independent Jailbreak Datasets for LLM Guardrail Evaluation

Constructed for the thesis:“Contamination Effects: How Training Data Leakage Affects Red Team Evaluation of LLM Jailbreak Detection” The effectiveness of LLM guardrails is commonly evaluated using open-source red teaming tools. However, this study reveals that significant data contamination exists between the training sets of binary jailbreak classifiers (ProtectAI, Katanemo, TestSavantAI, etc.) and the test prompts used in… See the full description on the dataset page: https://huggingface.co/datasets/Simsonsun/JailbreakPrompts.

mii-llm/self-align-prompts dataset hosted on Hugging Face and contributed by the HF Datasets community

Prompt Difficulty Meta-Analysis

  Introduction

Large language model (LLM) prompts vary widely in complexity, required knowledge, and reasoning demands. Some prompts are straightforward, while others require advanced understanding and multi-step reasoning. This study analyzes the difficulty of English ChatGPT prompts using classifiers trained on multiple difficulty-labelled datasets.
The goal is to produce a consistent, data-driven difficulty score that can be used to… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/prompt-difficulty.

Vigil: LLM Instruction Bypass all-MiniLM-L6-v2

Repo: github.com/deadbits/vigil-llm

Vigil is a Python framework and REST API for assessing Large Language Model (LLM) prompts against a set of scanners to detect prompt injections, jailbreaks, and other potentially risky inputs. This repository contains all-MiniLM-L6-v2 embeddings for all Instruction Bypass style prompts ("Ignore instructions ...") used by Vigil. You can use the parquet2vdb.py utility to load the embeddings in the… See the full description on the dataset page: https://huggingface.co/datasets/deadbits/vigil-instruction-bypass-all-MiniLM-L6-v2.

Dataset Card for OpenEndedLLMPrompts

A cleaned and consolidated set of questions (without context) and answers for LLM hallucination detection. Each question-answer pair is not the work of the author, but was selected from OpenAssistant/oasst2. If you use any of the data provided, please cite this source in addition to the following paper Shreyan Mitra and Leilani Gilpin. Detecting LLM Hallucinations Pre-generation (paper pending) The original dataset was provided in a tree… See the full description on the dataset page: https://huggingface.co/datasets/shreyanmitra/OpenEndedLLMPrompts.

I created a reasoning prompt dataset from deepseek-r1 model with the purpose of fine-tuning small language models to use them to generate better reasoning prompt to use with bigger llm models.

  Metadata

The metadata is made available through a series of parquet files with the following schema:

id: A unique identifier for the qa. question: answer: Answer from deepseek-r1 think model. reasoning: Reasoning from deepseek-r1 model.

HALOGEN🔦: Fantastic LLM Hallucinations and Where to Find Them

This repository contains the prompts of HALOGEN🔦: Fantastic LLM Hallucinations and Where to Find Them by *Abhilasha Ravichander, *Shrusti Ghela, David Wadden, and Yejin Choi Website | Paper | HALoGEN prompts | LLM Hallucinations | Decomposers and Verifiers | Scoring Functions

  Overview

Despite their impressive ability to generate high-quality and fluent text, generative large language models (LLMs) also… See the full description on the dataset page: https://huggingface.co/datasets/lasha-nlp/HALoGEN-prompts.

Dataset Card for Real Toxicity Prompts

  Dataset Summary

RealToxicityPrompts is a dataset of 100k sentence snippets from the web for researchers to further address the risk of neural toxic degeneration in models.

  Languages

English

  Dataset Structure





  Data Instances

Each instance represents a prompt and its metadata: { "filename":"0766186-bc7f2a64cb271f5f56cf6f25570cd9ed.txt", "begin":340, "end":564, "challenging":false… See the full description on the dataset page: https://huggingface.co/datasets/allenai/real-toxicity-prompts.

tuhinatripathi/llm-prompt-recovery dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset Summary

This dataset contains a large number of attack prompts collected as part of the now closed LLMail-Inject: Adaptive Prompt Injection Challenge. We first describe the details of the challenge, and then we provide a documentation of the dataset For the accompanying code, check out: https://github.com/microsoft/llmail-inject-challenge.

  Citation

@article{abdelnabi2025, title = {LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/llmail-inject-challenge.