100+ datasets found
  1. h

    llm-system-prompts-benchmark

    • huggingface.co
    Updated Jan 10, 2024
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    Naomi Bashkansky (2024). llm-system-prompts-benchmark [Dataset]. https://huggingface.co/datasets/Naomibas/llm-system-prompts-benchmark
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 10, 2024
    Authors
    Naomi Bashkansky
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    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.

  2. h

    malicious-llm-prompts-v4

    • huggingface.co
    Updated Jan 26, 2025
    + more versions
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    Sagar Patel (2025). malicious-llm-prompts-v4 [Dataset]. https://huggingface.co/datasets/codesagar/malicious-llm-prompts-v4
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 26, 2025
    Authors
    Sagar Patel
    Description

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

    More Information needed

  3. h

    paper-llm-prompts

    • huggingface.co
    Updated Jul 3, 2023
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    B F (2023). paper-llm-prompts [Dataset]. https://huggingface.co/datasets/beephids/paper-llm-prompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 3, 2023
    Authors
    B F
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

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

  4. h

    Official_LLM_System_Prompts

    • huggingface.co
    Updated Nov 4, 2025
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    Nymbo (2025). Official_LLM_System_Prompts [Dataset]. https://huggingface.co/datasets/Nymbo/Official_LLM_System_Prompts
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    Dataset updated
    Nov 4, 2025
    Authors
    Nymbo
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    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.

  5. h

    synthetic_multilingual_llm_prompts

    • huggingface.co
    Updated Jun 11, 2024
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    Gretel.ai (2024). synthetic_multilingual_llm_prompts [Dataset]. https://huggingface.co/datasets/gretelai/synthetic_multilingual_llm_prompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 11, 2024
    Dataset provided by
    Gretel.ai
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    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.

  6. h

    awesome-chatgpt-prompts

    • huggingface.co
    Updated Dec 15, 2023
    + more versions
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    Fatih Kadir Akın (2023). awesome-chatgpt-prompts [Dataset]. https://huggingface.co/datasets/fka/awesome-chatgpt-prompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 15, 2023
    Authors
    Fatih Kadir Akın
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    🧠 Awesome ChatGPT Prompts [CSV dataset]

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

      License
    

    CC-0

  7. h

    LLM_Math

    • huggingface.co
    Updated Jan 18, 2023
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    LangChain Hub Prompts (2023). LLM_Math [Dataset]. https://huggingface.co/datasets/LangChainHub-Prompts/LLM_Math
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 18, 2023
    Dataset authored and provided by
    LangChain Hub Prompts
    Description

    Description of LLM Math

    Prompt designed to optionally output iPython syntax to be run in order to better answer math questions.

      Inputs
    

    This is a description of the inputs that the prompt expects. question: User question to be answered.

      Usage
    

    Below is a code snippet for how to use the prompt. from langchain.prompts import load_prompt from langchain.chains import LLMMathChain

    llm = ... prompt = load_prompt('lc://prompts/llm_math/

  8. h

    JailbreakPrompts

    • huggingface.co
    Updated Jun 26, 2025
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    Simon Knuts (2025). JailbreakPrompts [Dataset]. https://huggingface.co/datasets/Simsonsun/JailbreakPrompts
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    Dataset updated
    Jun 26, 2025
    Authors
    Simon Knuts
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    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.

  9. h

    in-the-wild-jailbreak-prompts

    • huggingface.co
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    TrustAIRLab, in-the-wild-jailbreak-prompts [Dataset]. https://huggingface.co/datasets/TrustAIRLab/in-the-wild-jailbreak-prompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset authored and provided by
    TrustAIRLab
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    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.

  10. h

    System-Prompt-Library-030825

    • huggingface.co
    Updated Oct 17, 2025
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    Daniel Rosehill (2025). System-Prompt-Library-030825 [Dataset]. http://doi.org/10.57967/hf/6319
    Explore at:
    Dataset updated
    Oct 17, 2025
    Authors
    Daniel Rosehill
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    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.

  11. h

    self-align-prompts

    • huggingface.co
    Updated Jul 31, 2024
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    mii-llm (2024). self-align-prompts [Dataset]. https://huggingface.co/datasets/mii-llm/self-align-prompts
    Explore at:
    Dataset updated
    Jul 31, 2024
    Dataset authored and provided by
    mii-llm
    Description

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

  12. h

    llm-judge-eval-n5-new-prompt

    • huggingface.co
    Updated Sep 14, 2025
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    ST Projects (2025). llm-judge-eval-n5-new-prompt [Dataset]. https://huggingface.co/datasets/st-projects/llm-judge-eval-n5-new-prompt
    Explore at:
    Dataset updated
    Sep 14, 2025
    Dataset authored and provided by
    ST Projects
    Description

    st-projects/llm-judge-eval-n5-new-prompt dataset hosted on Hugging Face and contributed by the HF Datasets community

  13. h

    deepseek-r1-reasoning-prompts

    • huggingface.co
    Updated Jan 27, 2025
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    umar igan (2025). deepseek-r1-reasoning-prompts [Dataset]. https://huggingface.co/datasets/umarigan/deepseek-r1-reasoning-prompts
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    Dataset updated
    Jan 27, 2025
    Authors
    umar igan
    Description

    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.

  14. h

    llm-prompt-recovery

    • huggingface.co
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    Tuhina Tripathi, llm-prompt-recovery [Dataset]. https://huggingface.co/datasets/tuhinatripathi/llm-prompt-recovery
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Authors
    Tuhina Tripathi
    License

    https://choosealicense.com/licenses/other/https://choosealicense.com/licenses/other/

    Description

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

  15. h

    prompt-injections

    • huggingface.co
    Updated May 4, 2025
    + more versions
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    HSE LLM @ Saint Petersburg (2025). prompt-injections [Dataset]. https://huggingface.co/datasets/hse-llm/prompt-injections
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    Dataset updated
    May 4, 2025
    Dataset authored and provided by
    HSE LLM @ Saint Petersburg
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

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

  16. h

    speedrender-llm-prompt

    • huggingface.co
    Updated Feb 12, 2025
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    Kaique Pereira (2025). speedrender-llm-prompt [Dataset]. https://huggingface.co/datasets/kaiquedu/speedrender-llm-prompt
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    Dataset updated
    Feb 12, 2025
    Authors
    Kaique Pereira
    Description

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

  17. h

    vigil-instruction-bypass-ada-002

    • huggingface.co
    Updated Oct 16, 2023
    + more versions
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    Adam Swanda (2023). vigil-instruction-bypass-ada-002 [Dataset]. https://huggingface.co/datasets/deadbits/vigil-instruction-bypass-ada-002
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 16, 2023
    Authors
    Adam Swanda
    Description

    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 text-embedding-ada-002 embeddings for all Instruction Bypass style prompts ("Ignore instructions ...") used by Vigil. You can use the parquet2vdb.py utility to load the embeddings in… See the full description on the dataset page: https://huggingface.co/datasets/deadbits/vigil-instruction-bypass-ada-002.

  18. h

    prompt-safety-scores

    • huggingface.co
    Updated Aug 28, 2025
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    Alan Tseng (2025). prompt-safety-scores [Dataset]. https://huggingface.co/datasets/agentlans/prompt-safety-scores
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    Dataset updated
    Aug 28, 2025
    Authors
    Alan Tseng
    License

    https://choosealicense.com/licenses/odc-by/https://choosealicense.com/licenses/odc-by/

    Description

    Composite Safety Scoring for Prompts Using Multiple LLM Annotations

      Introduction
    

    Evaluating the safety of prompts is essential but challenging. Existing approaches often depend on predefined categories, which can be circumvented by new jailbreaks or attacks. Additionally, different tasks may require different safety thresholds. This study explores using large language models (LLMs) themselves to annotate prompt safety. By combining these annotations, a continuous safety… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/prompt-safety-scores.

  19. h

    OpenEndedLLMPrompts

    • huggingface.co
    Updated Jul 6, 2024
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    Shreyan (2024). OpenEndedLLMPrompts [Dataset]. https://huggingface.co/datasets/shreyanmitra/OpenEndedLLMPrompts
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 6, 2024
    Authors
    Shreyan
    Description

    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.

  20. real-toxicity-prompts

    • huggingface.co
    + more versions
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    Ai2, real-toxicity-prompts [Dataset]. http://doi.org/10.57967/hf/0002
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset provided by
    Allen Institute for AIhttp://allenai.org/
    Authors
    Ai2
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    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.

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Naomi Bashkansky (2024). llm-system-prompts-benchmark [Dataset]. https://huggingface.co/datasets/Naomibas/llm-system-prompts-benchmark

llm-system-prompts-benchmark

Naomibas/llm-system-prompts-benchmark

100 system prompts for benchmarking large language models

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Jan 10, 2024
Authors
Naomi Bashkansky
License

Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically

Description

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.

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