datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Glot500
Glot500 Corpus
A dataset of natural language data collected by putting together more than 150
existing mono-lingual and multilingual datasets together and crawling known multilingual websites.
The focus of this dataset is on 500 extremely low-resource languages.
(More Languages still to be uploaded here)
This dataset is used to train the Glot500 model.
Homepage: homepage
Repository: github
Paper: acl, arxiv
This dataset has the identical data format as the Taxi1500 Raw Data… See the full description on the dataset page: https://huggingface.co/datasets/cis-lmu/Glot500.lambada
Dataset Card for LAMBADA
Dataset Summary
The LAMBADA evaluates the capabilities of computational models
for text understanding by means of a word prediction task.
LAMBADA is a collection of narrative passages sharing the characteristic
that human subjects are able to guess their last word if
they are exposed to the whole passage, but not if they
only see the last sentence preceding the target word.
To succeed on LAMBADA, computational models cannot
simply rely on local… See the full description on the dataset page: https://huggingface.co/datasets/cimec/lambada.CircuitSense
CircuitSense
This dataset is a comprehensive multimodal circuit question-answering benchmark designed to evaluate visual reasoning and problem-solving capabilities across three main domains: Perception, Analysis, and Design. The dataset contains structured question-answer pairs with accompanying visual content, targeting different engineering cognitive levels and reasoning tasks.
Dataset Structure
The dataset is organized into three primary folders, each containing… See the full description on the dataset page: https://huggingface.co/datasets/armanakbari4/CircuitSense.civil_comments
Dataset Card for "civil_comments"
Dataset Summary
The comments in this dataset come from an archive of the Civil Comments
platform, a commenting plugin for independent news sites. These public comments
were created from 2015 - 2017 and appeared on approximately 50 English-language
news sites across the world. When Civil Comments shut down in 2017, they chose
to make the public comments available in a lasting open archive to enable future
research. The original data… See the full description on the dataset page: https://huggingface.co/datasets/google/civil_comments.TextPecker-1.5M
TextPecker-1.5M: A Dataset for Training and evaluating TextPecker
This repository contains the TextPecker-1.5M dataset, a new benchmark proposed in the paper "TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Rendering".
Code and Project Page
The official implementation and project details for the TextPecker and TextPecker-1.5M dataset can be found on the GitHub repository:
https://github.com/CIawevy/TextPecker
Sample Usage
You… See the full description on the dataset page: https://huggingface.co/datasets/CIawevy/TextPecker-1.5M.CI-VID
📄 CI-VID: A Coherent Interleaved Text-Video Dataset
CI-VID is a large-scale dataset designed to advance coherent multi-clip video generation. Unlike traditional text-to-video (T2V) datasets with isolated clip-caption pairs, CI-VID supports text-and-video-to-video (TV2V) generation by providing over 340,000 interleaved sequences of video clips and rich captions. It enables models to learn both intra-clip content and inter-clip transitions, fostering story-driven generation with… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/CI-VID.cissp-llmbench
CISSP-LLMBench
dmi-aarhus-weather-data
DMI Aarhus Weather Data
Training data and model artifact dataset for the Aarhus weather pipeline. Maintained by Ciroc0.
Primary files
File
Purpose
Produced by
training_matrix.parquet
Current source of truth for training rows and causal observation context
dmi-collector
model_registry.json
Active bucket registry per target
dmi-ml-trainer
model_meta.json
Training timestamp, sample count and training window
dmi-ml-trainer
temperature_models.pkl… See the full description on the dataset page: https://huggingface.co/datasets/Ciroc0/dmi-aarhus-weather-data.CICIoT2023Small
CICIoT2023
This dataset provides a processed derivative of the CICIoT2023 traffic collection. The repository organizes truncated PCAP files and flow-based CSV extractions aligned to the original CICResearch folder hierarchy.
Processing Workflow
The processing pipeline follows four stages:
Source acquisition from the CICResearch CICIoT2023 portal.
Flow extraction from full PCAP files using TriFlowMeter.
PCAP size reduction by truncating packet payloads to 128 bytes with… See the full description on the dataset page: https://huggingface.co/datasets/somnath0100/CICIoT2023Small.cifar100-pythonGlotCC-V1
Dataset Summary
GlotCC-V1.0 is a document-level, general domain dataset derived from CommonCrawl, covering more than 1000 languages.It is built using the GlotLID language identification and Ungoliant pipeline from CommonCrawl.We release our pipeline as open-source at https://github.com/cisnlp/GlotCC.
List of Languages: See https://datasets-server.huggingface.co/splits?dataset=cis-lmu/GlotCC-V1 to get the list of splits available.
Usage (Huggingface Hub -- Recommended)… See the full description on the dataset page: https://huggingface.co/datasets/cis-lmu/GlotCC-V1.Taxi1500-RawData
Taxi1500 Raw Data
Introduction
This repository contains the raw text data of the Taxi1500-c_v3.0 corpus, without classification labels and Bible verse ids. For the original Taxi1500 dataset for Text Classification, please refer to the GitHub repository.
The data format of the Taxi1500-RawData is identical to that of the Glot500 Dataset, facilitating seamless parallel utilization of both datasets.
Usage
Replace acr_Latn with your specific language.
from… See the full description on the dataset page: https://huggingface.co/datasets/cis-lmu/Taxi1500-RawData.pipeline_automation
Circuit Tracing Automation: LLMs can annotate attribution graphs
Custom automation pipeline on top of the circuit-tracer library. Automatically generates feature descriptions, supernodes, and validation scores for an attribution graph.
Repository Structure
prompts/ # Prompt datasets (shared across models)
prompts_capital.csv # Input prompts for attribution
ground_truth_capital.csv # Correct answers + intermediate… See the full description on the dataset page: https://huggingface.co/datasets/circuit-tracer-automation/pipeline_automation.Cifer-Fraud-Detection-Dataset-AF
📊 Cifer Fraud Detection Dataset
🧠 Overview
The Cifer-Fraud-Detection-Dataset-AF is a high-fidelity, fully synthetic dataset created to support the development and benchmarking of privacy-preserving, federated, and decentralized machine learning systems in financial fraud detection.
This dataset draws structural inspiration from the PaySim simulator, which was built using aggregated mobile money transaction data from a real financial provider operating in 14+ countries.… See the full description on the dataset page: https://huggingface.co/datasets/CiferAI/Cifer-Fraud-Detection-Dataset-AF.cic-ids-2017
CIC-IDS-2017 Dataset
This repository contains the CIC-IDS-2017 dataset with the original PCAPs and the CSVs converted to Parquet format for easier use.
Dataset Structure
Configurations
machine_learning: Contains the flow-based features used for ML training (Converted from MachineLearningCVE CSVs).
traffic_labels: Contains the labelled flows (Converted from TrafficLabelling CSVs). Timestamps have been normalized to UTC.
Raw Data
The pcap/ folder… See the full description on the dataset page: https://huggingface.co/datasets/bvsam/cic-ids-2017.glue-ci
Dataset Card for GLUE
Dataset Summary
GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural language understanding systems.
Supported Tasks and Leaderboards
The leaderboard for the GLUE benchmark can be found at this address. It comprises the following tasks:
ax
A manually-curated evaluation dataset for fine-grained analysis of system… See the full description on the dataset page: https://huggingface.co/datasets/evaluate/glue-ci.S10-Citadel-Core
Run and deploy your AI Studio app
This contains everything you need to run your app locally.
Run Locally
Prerequisites: Node.js
Install dependencies:
npm install
Set the GEMINI_API_KEY in .env.local to your Gemini API key
Run the app:
npm run dev
circleci-test-resultswds_vtab-cifar10MMSearch-Plus
MMSearch-Plus✨: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents
Official repository for the paper "MMSearch-Plus: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents".
🌟 For more details, please refer to the project page with examples: https://mmsearch-plus.github.io/.
[🌐 Webpage] [📖 Paper] [🤗 Huggingface Dataset] [🏆 Leaderboard]
💥 News
[2025.09.26] 🔥 We update the arXiv paperand release all MMSearch-Plus data samples in… See the full description on the dataset page: https://huggingface.co/datasets/Cie1/MMSearch-Plus.CIMA-4.8-ADR
CIMA Sección 4.8 — Reacciones Adversas
Corpus de texto biomédico regulatorio en español compuesto por la
sección 4.8 ("Reacciones adversas") de la totalidad de las fichas
técnicas publicadas por la
Agencia Española de Medicamentos y Productos Sanitarios (AEMPS)
en su Centro de Información Online de Medicamentos
(CIMA).
Este recurso fue construido como base para el pre-entrenamiento
adaptado al dominio (continued pre-training / domain-adaptive
pre-training, DAPT) de modelos… See the full description on the dataset page: https://huggingface.co/datasets/guerrerotook/CIMA-4.8-ADR.cifar100-enrichedThe CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).mmlu-cs
Czech MMLU
This is a Czech translation of the original MMLU dataset, created using the WMT 21 En-X model.
The 'auxiliary_train' subset is not included.
The translation was completed for use within the Czech-Bench evaluation framework.
The script used for translation can be reviewed here.
Citation
Original dataset:
@article{hendryckstest2021,
title={Measuring Massive Multitask Language Understanding},
author={Dan Hendrycks and Collin Burns and Steven Basart and… See the full description on the dataset page: https://huggingface.co/datasets/CIIRC-NLP/mmlu-cs.Dr-CiK
Dr-CiK: A Testbed for Foresight-Driven Agents
Dr-CiK is a benchmark for evaluating whether agents can retrieve
forecasting-relevant context from a noisy document corpus, filter out
distractors, distill the retrieved context into forecast-useful evidence, and
produce forecasts grounded in that evidence.
Real-world time-series forecasting often depends not only on historical
observations but also on external context that must be actively discovered
from heterogeneous, noisy… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow/Dr-CiK.Compact_OpenAIRE_citation_graph
📚 Compact OpenAIRE Citation Graph
Based on OpenAIRE Graph v11.1.1 (source on Zenodo).
The complete OpenAIRE citation graph, distilled into a handful of compact, analysis-ready files — the full scholarly citation network of the open-science ecosystem, small enough to actually work with.
Citation graphs at this scale are usually locked behind multi-terabyte dumps and heavyweight infrastructure. This dataset makes the entire OpenAIRE citation network loadable… See the full description on the dataset page: https://huggingface.co/datasets/Zmeos/Compact_OpenAIRE_citation_graph.cif-dataset
Cracks in the Foundation
A civil-infrastructure visual inspection dataset for instance segmentation with 6 defect/condition categories:
Algae · Crack · Net-Crack · Crack with Precipitation · Rust · Spalling
Each sample is either a full-resolution inspection image or a 1024×1024 tile derived from one.
Tiled samples carry extra fields (tile_row, tile_col, file_name_original, …) that are None for full-resolution samples.
Splits
Each split is its own parquet shard and… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/cif-dataset.wds_vtab-cifar100citations
Common Crawl Citations Overview
This dataset contains citations referencing Common Crawl Foundation and its datasets, pulled from Google Scholar.
Please note that these citations are not curated, so they will include some false positives. An annotated subset of these citations with additional fields can be found at cc-citations.
CIC-IDS2017The CICIDS2017 dataset consists of labeled network flows, including full packet payloads in pcap format, the corresponding profiles and the labeled flows (GeneratedLabelledFlows.zip) and CSV files for machine and deep learning purpose (MachineLearningCSV.zip) are publicly available for researchers. If you are using our dataset, you should cite our related paper which outlining the details of the dataset and its underlying principles:
Iman Sharafaldin, Arash Habibi Lashkari, and Ali A.… See the full description on the dataset page: https://huggingface.co/datasets/c01dsnap/CIC-IDS2017.circa
Dataset Card for CIRCA
Dataset Summary
The Circa (meaning ‘approximately’) dataset aims to help machine learning systems to solve the problem of interpreting indirect answers to polar questions.
The dataset contains pairs of yes/no questions and indirect answers, together with annotations for the interpretation of the answer. The data is collected in 10 different social conversational situations (eg. food preferences of a friend).
The following are the situational… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/circa.