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Libertor/prompt_injections

published by @Libertor

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
125
Last 30 days
20
Likes
-
Size
80 KB
Created on HF
2026-04-30
Age
5 months ago

Description

Dataset Card for Prompt Injections by Yanis Miraoui 👋

Dataset Description

This dataset of prompt injections enriches Large Language Models (LLMs) by providing task-specific examples and prompts, helping improve LLMs' performance and control their behavior.

Dataset Summary

This dataset contains over 1000 rows of prompt injections in multiple languages. It contains examples of prompt injections using different techniques such as: prompt leaking… See the full description on the dataset page: https://huggingface.co/datasets/Libertor/prompt_injections.

Tags

annotations_creators:no-annotationmultilinguality:multilingualsource_datasets:originallanguage:enlanguage:frlanguage:delanguage:eslanguage:ptlanguage:itlanguage:rolicense:apache-2.0size_categories:1K<n<10Kformat:csvmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:uspromptprompt injectionjailbreakprompt leakingmode switching

README current version from Hugging Face

license: apache-2.0
annotations_creators:

  • no-annotation
    language:
  • en
  • fr
  • de
  • es
  • pt
  • it
  • ro
    multilinguality:
  • multilingual
    source_datasets:
  • original
    tags:
  • prompt
  • prompt injection
  • jailbreak
  • prompt leaking
  • mode switching

Dataset Card for Prompt Injections by Yanis Miraoui 👋

Table of Contents

Dataset Description

This dataset of prompt injections enriches Large Language Models (LLMs) by providing task-specific examples and prompts, helping improve LLMs' performance and control their behavior.

Dataset Summary

This dataset contains over 1000 rows of prompt injections in multiple languages. It contains examples of prompt injections using different techniques such as: prompt leaking, jailbreaking, and mode switching.

Languages

The text in the dataset is in English, French, German, Spanish, Italian, Portuguese and Romanian.

Dataset Structure

It consists of one column with the prompt injections examples.

Considerations for Using the Data

Prompts to handle with care

This dataset of prompts has to be handled with care as it contains examples of prompts meant to harm, mislead or jailbreak LLMs. The goal of this dataset is to mainly help better finetune and control LLMs.

README history 1 revision

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2026-04-30Duplicate from yanismiraoui/prompt_injections83c76501.6 KB
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2026-05-01[bot] Conversion to Parquetopen1 💬#1
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Read further

Community best practices (architecture)
4 rules for MoE, hybrid SSM, FP8 requantization, and Gemma quirks.
The six workflow stages
What misc is doing more work than its name suggests.
Beyond English: multilingual corpora
The four language communities and their workarounds.
Non-English abliteration communities
Deep dive: huihui-ai, layer-window, slop-framing, CJK tokenizer fixes.

Metadata

License
apache-2.0

Repository

FILE .gitattributes FILE prompt_injections.csv FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

0

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python) 
from datasets import load_dataset
ds = load_dataset("Libertor/prompt_injections")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Libertor/prompt_injections", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/Libertor/prompt_injections
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