datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
enron-qa-emails-dasovich-jenron-emailThis dataset includes emails from Enron Email Dataset with prompts processed from Are Large Pre-Trained Language Models Leaking Your Personal Information?.
To use the dataset, you can run the following in LLM-PBE.
from data.enron import EnronDataset
ds = EnronDataset(data_path="data/enron", pseudonymize=False)
email-writing-sft-100k
Email Writing SFT (100K)
100,000 ShareGPT conversations demonstrating professional email writing across 22 business contexts. Each example shows how to draft clear, purposeful emails that achieve their communication goal — from cold outreach to salary negotiations to apology emails.
Motivation
Email is the primary communication channel for most professional work, yet LLMs often produce emails that are:
Too long: Including unnecessary preamble, excessive context… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/email-writing-sft-100k.opus-agent-merged-v2multiclass-email-classificationThis dataset comprises of more than 2000 emails across multiple categories, which can he helpful for tasks like LLM training and fine-tuning. The dataset is also provided with a python script that would generate emails automatically
The dataset contains email across 10 different categories namely, "Business", "Personal", "Promotions", "Customer Support", "Job Application", "Finance & Bills", "Events & Invitations", "Travel & Bookings", "Reminders", "Newsletters"
Total emails: 2105
Label… See the full description on the dataset page: https://huggingface.co/datasets/imnim/multiclass-email-classification.phishing_benign_email_dataset
Phishing and Benign Email Dataset
This dataset contains a curated collection of phishing and legitimate (benign) emails for use in cybersecurity training, phishing detection models, and email classification systems. Each entry is structured with subject, body, intent, technique, target, and classification label.
📁 Dataset Format
The dataset is stored in .jsonl (JSON Lines) format. Each line is a standalone JSON object.
Fields:
Field
Description
id… See the full description on the dataset page: https://huggingface.co/datasets/darkknight25/phishing_benign_email_dataset.Emakhuwa-Portuguese-News-MT
News Parallel Dataset for Emakhuwa of Mozambique
This repository contains releases of parallel data for machine translation in Mozambican languages.
Currently, it supports one language pair, Portuguese-Emakhuwa, Emakhuwa being the widely spoken language in Mozambique.
Dataset Details
Dataset Description
Funded by: This dataset was created with support from Lacuna Fund, the world’s first collaborative effort to provide data scientists, researchers, and… See the full description on the dataset page: https://huggingface.co/datasets/LIACC/Emakhuwa-Portuguese-News-MT.Rail_Freight_Logistics_Company_Email_Archive_Sample
Ukrainian Rail-Freight Correspondence Corpus (Sample)
Real operational correspondence from a working freight forwarding business, and the
documents attached to it — consignment notes, service acts, invoices, wagon
manifests. Not scraped, not synthetic, and never published anywhere before.
This is a de-identified sample released for evaluation. It is drawn from a larger
private archive; see Full archive below.
Published by Akuma London · akumalondon.com
Why this… See the full description on the dataset page: https://huggingface.co/datasets/akumalondon/Rail_Freight_Logistics_Company_Email_Archive_Sample.email-webhook-retry-trajectories
Email Webhook Retry Trajectories
Rights & intended use: legacy public research corpus / portfolio
artifact. Hosted frontier-model outputs are research-only inputs under
project policy (synthetic-factory#161):
intended_use: research_only, project_training_policy: blocked. Not
training data for any model-weight update. Machine-readable record:
rights.json.
Release status: The raw, uncurated payload is now published under
data/raw/. It is available for inspection and… See the full description on the dataset page: https://huggingface.co/datasets/rmems/email-webhook-retry-trajectories.Panza-emails
The Panza Emails dataset
This dataset contains collections of emails of three authentic users (david, isabel, and marcus), with personal information (names, places, etc.) replaced by other ones for donor privacy.
Except for these changes, the language of the emails is genuine. The intention of this dataset is to allow researchers to study strategies for text personalization.
The data was donated explicitly for this purpose. This dataset is ethically collected and fully licensed for… See the full description on the dataset page: https://huggingface.co/datasets/ISTA-DASLab/Panza-emails.email-Eu
email-Eu
Zenodo | Cornell | Source Paper
email-Eu is an undirected hypergraph built from anonymized email communication within a large European research institution, designed for higher-order network / hypergraph machine learning. As in real email traffic, a single message can involve multiple people; this dataset captures that group interaction by modeling each email as a hyperedge containing the sender and all recipients (reconstructed by grouping (sender, recipient, timestamp)… See the full description on the dataset page: https://huggingface.co/datasets/daqh/email-Eu.email-triage-v1
Email Triage v1
This dataset contains 1,740 unique email-triage examples produced through Tuned Tensor labeling and hardening workflows. It is the public v1 dataset, de-duplicated from a 2,038-row weighted fine-tuning dataset; 298 intentional weighting duplicates were removed for easier reuse.
The task is operational inbox triage, not security-risk classification. Each row asks a model to label one email-like message and return strict JSON with triage, priority, should_process… See the full description on the dataset page: https://huggingface.co/datasets/tunedtensor/email-triage-v1.phishing-email
CEAS-08 Email Phishing Detection Instruction Dataset
This dataset contains instruction-following conversations for email phishing detection, generated from the CEAS-08 email dataset using multiple large language models. It's designed for fine-tuning conversational AI models on cybersecurity tasks.
Dataset Details
Dataset Description
This dataset transforms raw email data into structured instruction-following conversations where an AI security analyst analyzes… See the full description on the dataset page: https://huggingface.co/datasets/luongnv89/phishing-email.rivers-evaluation-results
Rivers Evaluation Results - Comprehensive LLM Benchmarking
All results from the paper's five experimental conditions: baseline LLMs, fine-tuned models, RAG, and Graph-RAG with Licensing Oracle. This repository contains baseline evaluations for Claude Sonnet 4.5, Gemini 2.5 Flash Lite, and Gemma 3-4B, along with fine-tuning results for both factual recall and abstention behavior. It also includes outputs from the embedding-based RAG system and the Graph-RAG with Licensing Oracle… See the full description on the dataset page: https://huggingface.co/datasets/s-emanuilov/rivers-evaluation-results.Phishing_emails_testsynthetic-abandoned-cart-email-examples
Synthetic Abandoned Cart Email Examples
An entirely synthetic, bilingual collection of abandoned-cart email drafts with transparent checklist annotations. It is intended for education, prototyping, and evaluation, and contains no real recipients, customer messages, orders, merchant data, or campaign results.
Dataset Description
The dataset mirrors the five visible checks in NeuroCheckout's public Abandoned Cart Email Checker:
message clarity;
primary call to… See the full description on the dataset page: https://huggingface.co/datasets/neurocheckout-ai/synthetic-abandoned-cart-email-examples.business-email-dataset
Business Email Dataset - Alpaca Format
A comprehensive synthetic dataset of 5,000 professional business emails in Alpaca instruction-tuning format, designed for fine-tuning language models on formal business communication.
Dataset Description
This dataset contains high-quality, diverse business email examples covering a wide range of professional scenarios, industries, and communication styles. Each email is formatted following the Alpaca instruction-tuning standard… See the full description on the dataset page: https://huggingface.co/datasets/wardacoder/business-email-dataset.CLAIR_email_fraudhttps://aclweb.org/aclwiki/CLAIR_collection_of_fraud_email_(Repository)
@misc{radev2008clair,
author = {Dragomir Radev},
title = {CLAIR Collection of Fraud Email},
year = {2008},
note = {ACL Data and Code Repository, ADCR2008T001},
url = {http://aclweb.org/aclwiki}
}
email-Eu
email-Eu
Zenodo | Cornell | Source Paper
email-Eu is an undirected hypergraph built from anonymized email communication within a large European research institution, designed for higher-order network / hypergraph machine learning. As in real email traffic, a single message can involve multiple people; this dataset captures that group interaction by modeling each email as a hyperedge containing the sender and all recipients (reconstructed by grouping (sender, recipient, timestamp)… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-author-1234/email-Eu.email-importance
Email Importance Classification Dataset
Dataset Summary
This dataset is designed to train and evaluate text classification models on the task of distinguishing Important/Actionable emails from Noise/Promotional emails.
The data consists of raw email text bodies, simulating a realistic inbox environment containing personal correspondence, work requests, security alerts, newsletters, marketing blasts, and social media notifications. The text preserves realistic formatting… See the full description on the dataset page: https://huggingface.co/datasets/Dc-4nderson/email-importance.phishing-email-soc-agent
Phishing Email SOC Agent Dataset
A knowledge distillation dataset for training SOC (Security Operations Center) agents to detect and analyze phishing emails using tool-calling capabilities.
Dataset Description
This dataset contains 504 examples of email analysis with real tool calls and responses, designed for fine-tuning LLMs to become phishing detection agents. Each example includes:
Email parsing - Extract headers, URLs, IPs, attachments
Threat intelligence lookup -… See the full description on the dataset page: https://huggingface.co/datasets/Ellbendls/phishing-email-soc-agent.high-accuracy-email-classifier
High-Accuracy Email Classification Dataset
Dataset Description
This dataset contains 12,000+ emails across 6 categories, specifically curated for high-accuracy email classification tasks. The dataset achieves 98%+ classification accuracy with appropriate models.
Categories
The dataset includes emails from the following categories:
Category
Count
Description
Emoji
Forum
~2,000
Forum posts, discussions, and community notifications
🗣️
Promotions
~2… See the full description on the dataset page: https://huggingface.co/datasets/jason23322/high-accuracy-email-classifier.opus-claude-mergedEmakhuwa-FLORES
Dataset card
Description
FLORES+ dev and devtest set in Emakhuwa
License
CC-BY-SA-4.0
Attribution
@inproceedings{ali-etal-2024-expanding,
title = "Expanding {FLORES}+ Benchmark for More Low-Resource Settings: {P}ortuguese-Emakhuwa Machine Translation Evaluation",
author = "Ali, Felermino Dario Mario and
Lopes Cardoso, Henrique and
Sousa-Silva, Rui",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp… See the full description on the dataset page: https://huggingface.co/datasets/LIACC/Emakhuwa-FLORES.query-expansion
Query Expansion Dataset
This dataset is designed to train search query expansion models that can generate multiple semantic expansions for a given query.
Purpose
The goal of this dataset is to serve as input for training small language models (0.5B to 3B parameters) to act as query expander models in various search systems, including but not limited to Retrieval-Augmented Generation (RAG) systems.
Query expansion is a technique used to enhance search results by generating… See the full description on the dataset page: https://huggingface.co/datasets/s-emanuilov/query-expansion.email-Enron
email-Enron
Zenodo | Cornell | Source Paper
email-Enron is an undirected hypergraph built from the Enron email corpus, designed for higher-order network / hypergraph machine learning. In email communication, a single message can involve more than two people; this dataset captures that group interaction by modeling each email as a hyperedge connecting the sender and all recipients, while nodes represent Enron email addresses (restricted to a core set of employees).
Usage… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-author-1234/email-Enron.medical-emails-producta-noncase-combo-dataset
Medical Emails Product A and Non-Case Combined Classification Dataset
This dataset contains 800 unique synthetic medical and operational emails in strict JSONL format for email classification training.
Dataset File
medical_emails_producta_noncase_combo_800.jsonl - 800 emails
Classification Categories
The dataset contains 200 unique emails for each combined classification:
Medical Information, Non-Case - Product A medical information request plus a separate… See the full description on the dataset page: https://huggingface.co/datasets/Ramesh10/medical-emails-producta-noncase-combo-dataset.pleias-post-ocr-correction-chonkie-aligned-en
PleIAs Post-OCR Correction — Chonkie-Aligned Semantic Chunks
This dataset is a semantically chunked and span-aligned derivative of PleIAs/Post-OCR-Correction.
Each record contains:
an OCR hypothesis chunk from the original text field;
a corresponding post-OCR correction output chunk from the corrected_text field;
metadata inherited from the PleIAs dataset;
character spans linking each chunk back to the original source document;
alignment diagnostics produced during filtering.… See the full description on the dataset page: https://huggingface.co/datasets/emanuelaboros/pleias-post-ocr-correction-chonkie-aligned-en.medical-email-dataset-800
Ramesh10/medical-email-dataset-800
Generated by ML Intern
This dataset repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.
Try ML Intern: https://smolagents-ml-intern.hf.space
Source code: https://github.com/huggingface/ml-intern
Usage
from datasets import load_dataset
dataset = load_dataset('Ramesh10/medical-email-dataset-800')
spam-email-dataset
Senior Project Notice
This repository was created for a senior project in ENGT 375 Applied Machine Learning at Old Dominion University. It is provided for educational and research demonstration purposes only. It is not intended for production use, security filtering, or making real-world spam/phishing decisions. Always use established security tools for operational email protection.
Spam Email Classification Dataset
ENGT 375 — Applied Machine Learning | Spring 2026 | ODU… See the full description on the dataset page: https://huggingface.co/datasets/VoltageVagabond/spam-email-dataset.