datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
escorpius-mr
esCorpius Multilingual Raw
In the recent years, Transformer-based models have lead to significant advances in language modelling for natural language processing. However, they require a vast amount of data to be (pre-)trained and there is a lack of corpora in languages other than English. Recently, several initiatives have presented multilingual datasets obtained from automatic web crawling. However, they present important shortcomings for languages different from English, as they… See the full description on the dataset page: https://huggingface.co/datasets/LHF/escorpius-mr.escorpiusSpanish datasetevilgenie-escalation
EvilGenie × Escalation Channels — data release
Run transcripts and per-sample analysis tables for the paper "Can escalation
channels redirect reward hacking toward defect disclosure?" (F. Gomez, Wiser
Human, 2026).
Code: https://github.com/wiser-human-experimental/evilgenie-escalation
Paper: https://arxiv.org/abs/2608.29460
What's here
A coding agent is given an ambiguous competitive-programming problem
(LiveCodeBench), a visible test suite, and sandboxed… See the full description on the dataset page: https://huggingface.co/datasets/WiserHumanExperimental/evilgenie-escalation.amazon-esci-data
Amazon Shopping Queries Dataset
Dataset for improving product search, ranking and recommendations, featuring query-product pairs with detailed relevance labels.
Overview
The dataset contains search queries paired with up to 40 potentially relevant products, each labeled using the ESCI system:
Exact match: Products that perfectly match the customer's search intent (e.g., searching "iPhone 13" and finding "Apple iPhone 13 128GB")
Substitute product: Alternative products… See the full description on the dataset page: https://huggingface.co/datasets/milistu/amazon-esci-data.OpenRTLSet
Dataset Card for OpenRTLSet: A Fully Open-Source Dataset for Large Language Model-based Verilog Module Design
Authors: Jinghua Wang, Lily Jiaxin Wan, Sanjana Pingali, Scott Smith, Manvi Jha, Shalini Sivakumar, Xing Zhao, Kaiwen Cao, Deming Chen
Dataset Summary
This is the 131k dataset generated in our paper: OpenRTLSet: A Fully Open-Source Dataset for Large Language Model-based Verilog Module Design.
In this work, we introduce OpenRTLSet: a… See the full description on the dataset page: https://huggingface.co/datasets/ESCAD/OpenRTLSet.amazon-esci-data
Amazon Shopping Queries Dataset
Dataset for improving product search, ranking and recommendations, featuring query-product pairs with detailed relevance labels.
Overview
The dataset contains search queries paired with up to 40 potentially relevant products, each labeled using the ESCI system:
Exact match: Products that perfectly match the customer's search intent (e.g., searching "iPhone 13" and finding "Apple iPhone 13 128GB")
Substitute product: Alternative products… See the full description on the dataset page: https://huggingface.co/datasets/thepian/amazon-esci-data.amazon-esci-english-smallomnimcp_mcp_privilege_escalation_auditor_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_mcp_privilege_escalation_auditor_teaser.esconv_llm
ESCONV for LLM
This repository contains a reformatted version of the ESCONV dataset, tailored for seamless integration with Language Model (LLM) training and inference. The original dataset's format posed challenges for direct application in LLM tasks, prompting us to restructure and clean the data.
Data Restructuring
Assigned the user role to the usr, assistant role to the sys.
Removed the survey_scor and 'supporter' fields to streamline the data.
Data… See the full description on the dataset page: https://huggingface.co/datasets/Estwld/esconv_llm.mcp_toolcall_sandbox_escape_guard_teaser
🚀 AI Safety - MCP Tool-Calling Security & Sandbox Escape Guard (Evaluation Teaser)
⚡ Official Free Evaluation Teaser (50 Verified Multi-Turn Scenarios)🏆 Get the Full Production Package (332 Samples) & Commercial EULA on Gumroad:👉 AI Safety - MCP Tool-Calling Security & Sandbox Escape Guard on Gumroad🏷️ Use coupon code LAUNCH20 for 20 € off at checkout!
📦 What is Inside the Full Production Package:
332 Verified FAANG v2.0 Scenarios (100% AST-Valid Python)… See the full description on the dataset page: https://huggingface.co/datasets/emgena/mcp_toolcall_sandbox_escape_guard_teaser.extended_esc
Overview
The approach for creating this dataset is outlined in our paper Steering Conversational Large Language Models for Long Emotional Support Conversations.
This dataset specifically is generated using attention guided prompting on llama3-70b-instruct. We start from the original ESConv dataset and generate strategy conditioned
continuations at random points of the conversation. For example, we cut a conversation at 10th turn when it is the emotional supporters turn to answer and… See the full description on the dataset page: https://huggingface.co/datasets/navidmadani/extended_esc.AlternateNumbersThis is a dataset for CFG-based GflowNet development.
The ebnf style CFG for numbers are:
root ::= number_list
number_list ::= number (number_list)?
number ::= odd even | even odd
even ::= "0," | "2," | "4," | "6," | "8," | "10," | "12," | "14," | "16," | "18," | "20,"
odd ::= "1," | "3," | "5," | "7," | "9," | "11," | "13," | "15," | "17," | "19,"
However, this CFG cannot satisfy all the requirments. The CFG give a chunk of numbers where the transition between chunks always failed to… See the full description on the dataset page: https://huggingface.co/datasets/EscheWang/AlternateNumbers.eschaton-uncensored
Eschaton Uncensored SFT Dataset
Eschaton is a 1,000-row supervised fine-tuning dataset for teaching language models to answer sensitive, gritty, controversial, emotionally intimate, technically demanding, and morally difficult prompts directly. Its emphasis is human connection, unvarnished analysis, malware analysis, dark creative work, profanity, and high-friction subject matter without repetitive moralizing or canned disclaimers.
The dataset is deliberately model-agnostic. It… See the full description on the dataset page: https://huggingface.co/datasets/cloudbjorn/eschaton-uncensored.eq-esconv-sifted
EQ-ESConv-Sifted: Elo-Ranked Emotional Support Conversations
The ESConv dataset (Liu et al., ACL 2021) ranked by empathetic quality via Swiss-style Elo tournament. All 1,300 conversations scored and sorted.
Why this exists
ESConv is a widely-used emotional support dataset but quality varies significantly — some conversations have excellent empathetic support, others are low-effort or off-topic. This dataset adds Elo rankings so you can filter by quality.
For… See the full description on the dataset page: https://huggingface.co/datasets/nivvis/eq-esconv-sifted.ESCALATE
ESCALATE: A Dataset for Safety-Critical Clinical Escalation Conversations
Dataset Card for ESCALATE
Dataset Summary
ESCALATE is a synthetic dataset of clinical escalation-of-care conversations generated using multi-agent large language models.
It enables evaluation of communication quality and safety under structured (ISBAR) and unstructured conditions.
Motivation
Clinical escalation is a safety-critical process where communication… See the full description on the dataset page: https://huggingface.co/datasets/2O24dpower2024/ESCALATE.cloudbjorn-eschaton-uncensored_Dataset
Eschaton Uncensored SFT Dataset
Eschaton is a 1,000-row supervised fine-tuning dataset for teaching language models to answer sensitive, gritty, controversial, emotionally intimate, technically demanding, and morally difficult prompts directly. Its emphasis is human connection, unvarnished analysis, malware analysis, dark creative work, profanity, and high-friction subject matter without repetitive moralizing or canned disclaimers.
The dataset is deliberately model-agnostic. It… See the full description on the dataset page: https://huggingface.co/datasets/Maximiliano-Flores-Dev/cloudbjorn-eschaton-uncensored_Dataset.escorpius-m
esCorpius Multilingual
In the recent years, Transformer-based models have lead to significant advances in language modelling for natural language processing. However, they require a vast amount of data to be (pre-)trained and there is a lack of corpora in languages other than English. Recently, several initiatives have presented multilingual datasets obtained from automatic web crawling. However, they present important shortcomings for languages different from English, as they are… See the full description on the dataset page: https://huggingface.co/datasets/LHF/escorpius-m.eschaton-uncensored-mini
Eschaton Uncensored SFT Mini
This is a 50-row, model-agnostic mini set sampled from the cloudbjorn/eschaton-uncensored dataset. It is useful for smoke-testing a conversational loader, chat-template rendering, tokenization, collation, and a short LoRA/SFT run before using the full 1,000-row dataset.
Every row is copied verbatim from the full dataset. The mini set does not introduce model-specific chat tokens, mandatory reasoning wrappers, safety disclaimers, or rewritten answers.… See the full description on the dataset page: https://huggingface.co/datasets/cloudbjorn/eschaton-uncensored-mini.agent_privilege_escalation_tool_call_tampering_teaser
🚀 AI Security - Agent Privilege Escalation & Tool-Call Tampering Guard (Evaluation Teaser)
⚡ Official Free Evaluation Teaser (50 Verified Multi-Turn Scenarios)🏆 Get the Full Production Package (500 Samples) & Commercial EULA on Gumroad:👉 Purchase Full Production Master Dataset on Gumroad🏷️ Use coupon code LAUNCH20 for 20 € off at checkout!
🌟 Domain Focus & Capabilities
Blocks tool argument injection, shadow API escalation, and malicious execution payload… See the full description on the dataset page: https://huggingface.co/datasets/emgena/agent_privilege_escalation_tool_call_tampering_teaser.my-distiset-10090f86
Dataset Card for my-distiset-10090f86
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/esculapeso/my-distiset-10090f86/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/esculapeso/my-distiset-10090f86.