asoria/hf-datasets-descriptions · Datasets at Fast360

id stringlengths 6 121	author stringlengths 2 42	description stringlengths 0 6.67k
s-nlp/paradetox	s-nlp	ParaDetox: Text Detoxification with Parallel Data (English) This repository contains information about ParaDetox dataset -- the first parallel corpus for the detoxification task -- as well as models and evaluation methodology for the detoxification of English texts. The original paper "ParaDetox: Detoxification with Parallel Data" was presented at ACL 2022 main conference. 📰 Updates [2024] We have also created versions of ParaDetox in more languages. You can checkout a… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/paradetox.
NLPC-UOM/sentence_alignment_dataset-Sinhala-Tamil-English	NLPC-UOM	Dataset summary This is a gold-standard benchmark dataset for sentence alignment, between Sinhala-English-Tamil languages. Data had been crawled from the following news websites. The aligned documents annotated in the dataset NLPC-UOM/document_alignment_dataset-Sinhala-Tamil-English had been considered to annotate the aligned sentences. News Source url Army https://www.army.lk/ Hiru http://www.hirunews.lk ITN https://www.newsfirst.lk Newsfirst… See the full description on the dataset page: https://huggingface.co/datasets/NLPC-UOM/sentence_alignment_dataset-Sinhala-Tamil-English.
mteb/amazon_reviews_multi	mteb	We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language. For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long. Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.
sileod/movie_recommendation	sileod	Movie recommendation task based on the Movielens dataset
ganchengguang/resume_seven_class	ganchengguang	This is a resume sentence classification dataset constructed based on resume text.（https://www.kaggle.com/datasets/oo7kartik/resume-text-batch）The dataset have seven category.(experience education knowledge project others ) And three element label(header content meta).Because the dataset is a published paper, if you want to use this dataset in a paper or work, please cite following paper.https://arxiv.org/abs/2208.03219 And dataset use in article https://arxiv.org/abs/2209.09450
mteb/sts22-crosslingual-sts	mteb	Scores in this dataset have been inverted to be from least to most similar! The scores in the original STS22 task were from most to least similar. Updates: 2024/07/06: Removed pairs where one of the sentences is empty.
LTCB/enwik8	LTCB	The dataset is based on the Hutter Prize (http://prize.hutter1.net) and contains the first 10^8 bytes of English Wikipedia in 2006 in XML
lmqg/qg_koquad	lmqg	[KorQuAD](https://huggingface.co/datasets/squad_kor_v1) dataset for question generation (QG) task.
BeIR/msmarco	BeIR	Dataset Card for BEIR Benchmark Dataset Summary BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks: Fact-checking: FEVER, Climate-FEVER, SciFact Question-Answering: NQ, HotpotQA, FiQA-2018 Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus News Retrieval: TREC-NEWS, Robust04 Argument Retrieval: Touche-2020, ArguAna Duplicate Question Retrieval: Quora, CqaDupstack Citation-Prediction: SCIDOCS Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/msmarco.
Adapting/empathetic_dialogues_v2	Adapting	Fine-tuned empathetic dialogue datasets from https://huggingface.co/datasets/empathetic_dialogues With labeled chat history, system response, question or not and behavior.
AhmedSSabir/Japanese-wiki-dump-sentence-dataset	AhmedSSabir	Dataset 5M (5121625) clean Japanese full sentence with the context. This dataset can be used to learn unsupervised semantic similarity, etc.
truthfulqa/truthful_qa	truthfulqa	Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.
google/bigbench	google	The Beyond the Imitation Game Benchmark (BIG-bench) is a collaborative benchmark intended to probe large language models, and extrapolate their future capabilities.
Bingsu/Human_Action_Recognition	Bingsu	Dataset Summary A dataset from kaggle. origin: https://dphi.tech/challenges/data-sprint-76-human-activity-recognition/233/data Introduction The dataset features 15 different classes of Human Activities. The dataset contains about 12k+ labelled images including the validation images. Each image has only one human activity category and are saved in separate folders of the labelled classes PROBLEM STATEMENT Human Action Recognition (HAR) aims to… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/Human_Action_Recognition.
google/quickdraw	google	The Quick Draw Dataset is a collection of 50 million drawings across 345 categories, contributed by players of the game Quick, Draw!. The drawings were captured as timestamped vectors, tagged with metadata including what the player was asked to draw and in which country the player was located.
sil-ai/bloom-speech	sil-ai	Bloom-speech is a dataset of text aligned speech from bloomlibrary.org. This dataset contains over 50 languages including many low-resource languages. This dataset should be useful for training and/or testing speech-to-text or text-to-speech/ASR models.
speechcolab/gigaspeech	speechcolab	GigaSpeech is an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training, and 40,000 hours of total audio suitable for semi-supervised and unsupervised training. Around 40,000 hours of transcribed audio is first collected from audiobooks, podcasts and YouTube, covering both read and spontaneous speaking styles, and a variety of topics, such as arts, science, sports, etc. A new forced alignment and segmentation pipeline is proposed to create sentence segments suitable for speech recognition training, and to filter out segments with low-quality transcription. For system training, GigaSpeech provides five subsets of different sizes, 10h, 250h, 1000h, 2500h, and 10000h. For our 10,000-hour XL training subset, we cap the word error rate at 4% during the filtering/validation stage, and for all our other smaller training subsets, we cap it at 0%. The DEV and TEST evaluation sets, on the other hand, are re-processed by professional human transcribers to ensure high transcription quality.
SetFit/CR	SetFit	Customer Reviews This dataset is a port of the official CR dataset from this paper. There is no validation split.
demo-org/auditor_review	demo-org	Dataset Card for Auditor_Review Dataset Description Auditor review data collected by News Department Point of Contact: Talked to COE for Auditing, currently [email protected] Dataset Summary Auditor sentiment dataset of sentences from financial news. The dataset consists of 3500 sentences from English language financial news categorized by sentiment. The dataset is divided by the agreement rate of 5-8 annotators. Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/demo-org/auditor_review.
thu-coai/lccc	thu-coai	LCCC: Large-scale Cleaned Chinese Conversation corpus (LCCC) is a large corpus of Chinese conversations. A rigorous data cleaning pipeline is designed to ensure the quality of the corpus. This pipeline involves a set of rules and several classifier-based filters. Noises such as offensive or sensitive words, special symbols, emojis, grammatically incorrect sentences, and incoherent conversations are filtered.
julien-c/kaggle-hugomathien-soccer	julien-c	Source: https://www.kaggle.com/datasets/hugomathien/soccer by Hugo Mathien About Dataset The ultimate Soccer database for data analysis and machine learning What you get: +25,000 matches +10,000 players 11 European Countries with their lead championship Seasons 2008 to 2016 Players and Teams' attributes* sourced from EA Sports' FIFA video game series, including the weekly updates Team line up with squad formation (X, Y coordinates) Betting odds from up to 10… See the full description on the dataset page: https://huggingface.co/datasets/julien-c/kaggle-hugomathien-soccer.
valurank/Adult-content-dataset	valurank	Dataset Card for Adult_Content_Detection Dataset Description 850 Articles descriptions classified into two different categories namely: Adult, and Non_Adult Languages The text in the dataset is in English Dataset Structure The dataset consists of two columns namely Description and Category. The Description column consists of the overview of the article and the Category column consists of the class each article belongs to… See the full description on the dataset page: https://huggingface.co/datasets/valurank/Adult-content-dataset.
mounikaiiith/Telugu-Sarcasm	mounikaiiith	Do cite the below references for using the dataset: @article{marreddy2022resource, title={Am I a Resource-Poor Language? Data Sets, Embeddings, Models and Analysis for four different NLP tasks in Telugu Language}, author={Marreddy, Mounika and Oota, Subba Reddy and Vakada, Lakshmi Sireesha and Chinni, Venkata Charan and Mamidi, Radhika}, journal={Transactions on Asian and Low-Resource Language Information Processing}, publisher={ACM New York, NY} } @article{marreddy2022multi… See the full description on the dataset page: https://huggingface.co/datasets/mounikaiiith/Telugu-Sarcasm.
HuggingFaceM4/Stanford-Cars	HuggingFaceM4	Code snippet to visualise the position of the box import matplotlib.image as img import matplotlib.pyplot as plt from datasets import load_dataset from matplotlib.patches import Rectangle # Load dataset ds_name = "SaulLu/Stanford-Cars" ds = load_dataset(ds_name, use_auth_token=True) # Extract information for the sample we want to show index = 100 sample = ds["train"][index] box_coord = sample["bbox"][0] img_path = sample["image"].filename # Create plot # define Matplotlib figure… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/Stanford-Cars.
Shayanvsf/pquad_public	Shayanvsf	\\\ParSQuAD: Persian Question Answering Dataset based on Machine Translation of SQuAD 2.0
Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder	Nexdata	Dataset Card for Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder Dataset Summary 995 local Cantonese speakers participated in the recording, and conducted face-to-face communication in a natural way. They had free discussion on a number of given topics, with a wide range of fields; the voice was natural and fluent, in line with the actual dialogue scene. Text is transferred manually, with high accuracy. For more details, please… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder.
iejMac/CLIP-Kinetics700	iejMac	Dataset Card for CLIP-Kinetics70 Dataset Description Dataset Summary CLIP-Kinetics700 is a compressed version of the Kinetics700 dataset using OpenAI's CLIP model. The original dataset is ~700 GB making it difficult to use and hold in memory on one machine. By downsampling each video to 1 FPS and encoding the frames using CLIP we we're able to compress the dataset to ~8 GB making it very memory-friendly and easy to use. Dataset… See the full description on the dataset page: https://huggingface.co/datasets/iejMac/CLIP-Kinetics700.
Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array	Nexdata	Dataset Card for Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array Dataset Summary The data consists of multiple sets of products, each with a different type of microphone arrays. Noise data is collected from real home scenes of the indoor residence of ordinary residents. The data set can be used for tasks such as voice enhancement and automatic speech recognition in a home scene. For more details, please refer to the link:… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array.
Nexdata/Emotional_Video_Data	Nexdata	Dataset Card for Nexdata/Emotional_Video_Data Dataset Summary 1,003 People - Emotional Video Data. The data diversity includes multiple races, multiple indoor scenes, multiple age groups, multiple languages, multiple emotions (11 types of facial emotions, 15 types of inner emotions). For each sentence in each video, emotion types (including facial emotions and inner emotions), start & end time, and text transcription were annotated.This dataset can be used for… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Emotional_Video_Data.
nateraw/parti-prompts	nateraw	Dataset Card for PartiPrompts (P2) Dataset Summary PartiPrompts (P2) is a rich set of over 1600 prompts in English that we release as part of this work. P2 can be used to measure model capabilities across various categories and challenge aspects. P2 prompts can be simple, allowing us to gauge the progress from scaling. They can also be complex, such as the following 67-word description we created for Vincent van Gogh’s The Starry Night (1889): Oil-on-canvas… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/parti-prompts.
CShorten/ML-ArXiv-Papers	CShorten	This dataset contains the subset of ArXiv papers with the "cs.LG" tag to indicate the paper is about Machine Learning. The core dataset is filtered from the full ArXiv dataset hosted on Kaggle: https://www.kaggle.com/datasets/Cornell-University/arxiv. The original dataset contains roughly 2 million papers. This dataset contains roughly 100,000 papers following the category filtering. The dataset is maintained by with requests to the ArXiv API. The current iteration of the dataset only contains… See the full description on the dataset page: https://huggingface.co/datasets/CShorten/ML-ArXiv-Papers.
fever/feverous	fever	Dataset Card for FEVEROUS Dataset Summary With billions of individual pages on the web providing information on almost every conceivable topic, we should have the ability to collect facts that answer almost every conceivable question. However, only a small fraction of this information is contained in structured sources (Wikidata, Freebase, etc.) – we are therefore limited by our ability to transform free-form text to structured knowledge. There is, however… See the full description on the dataset page: https://huggingface.co/datasets/fever/feverous.
stanfordnlp/concurrentqa	stanfordnlp	ConcurrentQA is a textual multi-hop QA benchmark to require concurrent retrieval over multiple data-distributions (i.e. Wikipedia and email data). This dataset was constructed by researchers at Stanford and FAIR, following the data collection process and schema of HotpotQA. This benchmark can be used to study generalization in retrieval as well as privacy when reasoning across multiple privacy scopes --- i.e. public Wikipedia documents and private emails. This dataset is for the… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/concurrentqa.
joelniklaus/brazilian_court_decisions	joelniklaus	Dataset Card for predicting-brazilian-court-decisions Dataset Summary The dataset is a collection of 4043 Ementa (summary) court decisions and their metadata from the Tribunal de Justiça de Alagoas (TJAL, the State Supreme Court of Alagoas (Brazil). The court decisions are labeled according to 7 categories and whether the decisions were unanimous on the part of the judges or not. The dataset supports the task of Legal Judgment Prediction. Supported… See the full description on the dataset page: https://huggingface.co/datasets/joelniklaus/brazilian_court_decisions.
rkstgr/mtg-jamendo	rkstgr	Repackaging of the MTG Jamendo dataset. We present the MTG-Jamendo Dataset, a new open dataset for music auto-tagging. It is built using music available at Jamendo under Creative Commons licenses and tags provided by content creators. The dataset contains over 55,000 full audio tracks with 195 tags from genre, instrument, and mood/theme categories.
HuggingFaceM4/VQAv2	HuggingFaceM4	VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to answer.
codeparrot/codecomplex	codeparrot	CodeComplex Dataset Dataset Description CodeComplex consists of 4,200 Java codes submitted to programming competitions by human programmers and their complexity labels annotated by a group of algorithm experts. How to use it You can load and iterate through the dataset with the following two lines of code: from datasets import load_dataset ds = load_dataset("codeparrot/codecomplex", split="train") print(next(iter(ds))) Data Structure… See the full description on the dataset page: https://huggingface.co/datasets/codeparrot/codecomplex.
Nexdata/Human_Facial_Skin_Defects_Data	Nexdata	Dataset Card for Nexdata/Human_Facial_Skin_Defects_Data Dataset Summary 4,788 Chinese people 5,105 images Human Facial Skin Defects Data. The data includes the following five types of facial skin defects: acne, acne marks, stains, wrinkles and dark circles. This data can be used for tasks such as skin defects detection. For more details, please refer to the link: https://www.nexdata.ai/datasets/computervision/1052?source=Huggingface Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Human_Facial_Skin_Defects_Data.
launch/open_question_type	launch	Open-ended question type annotated dataset.
knkarthick/samsum	knkarthick	Dataset Card for SAMSum Corpus Dataset Description Links Homepage: hhttps://arxiv.org/abs/1911.12237v2 Repository: https://arxiv.org/abs/1911.12237v2 Paper: https://arxiv.org/abs/1911.12237v2 Point of Contact: https://huggingface.co/knkarthick Dataset Summary The SAMSum dataset contains about 16k messenger-like conversations with summaries. Conversations were created and written down by linguists fluent in English. Linguists were… See the full description on the dataset page: https://huggingface.co/datasets/knkarthick/samsum.
kensho/spgispeech	kensho	The SPGISpeech corpus is derived from company earnings calls manually transcribed by S&P Global, Inc. according to a pro- fessional style guide detailing conventions for capitalization, punctuation, denormalization of non-standard words and tran- scription of disfluencies in spontaneous speech. The basic unit of SPGISpeech is a pair consisting of a 5 to 15 second long 16 bit, 16kHz mono wav audio file and its transcription..
codeparrot/github-code-clean	codeparrot	The GitHub Code clean dataset in a more filtered version of codeparrot/github-code dataset, it consists of 115M code files from GitHub in 32 programming languages with 60 extensions totaling in almost 1TB of text data.
zh-plus/tiny-imagenet	zh-plus	Dataset Card for tiny-imagenet Dataset Summary Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images. Languages The class labels in the dataset are in English. Dataset Structure Data Instances { 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190… See the full description on the dataset page: https://huggingface.co/datasets/zh-plus/tiny-imagenet.
benschill/brain-tumor-collection	benschill	This dataset is intended as a test case for classification tasks (4 different kinds of brain xrays). The dataset consists of almost 1400 JPEG images grouped into two splits - training and validation. Each split contains 4 categories labeled as n0~n3, each corresponding to a cancer result of the mrt. \| Label \| Xray Category \| Train Images \| Validation Images \| \| ----- \| --------------------- \| ------------ \| ----------------- \| \| n0 \| glioma_tumor \| 826 \| 100 \| \| n1 \| meningioma_tumor \| 822 \| 115 \| \| n2 \| pituitary_tumor \| 827 \| 74 \| \| n3 \| no_tumor \| 395 \| 105 \|
nreimers/reddit_question_best_answers	nreimers	Question & question body together with the best answers to that question from Reddit. The score for the question / answer is the upvote count (i.e. positive-negative upvotes). Only questions / answers that have these properties were extracted: min_score = 3 min_title_len = 20 min_body_len = 100
codeparrot/xlcost-text-to-code	codeparrot	XLCoST is a machine learning benchmark dataset that contains fine-grained parallel data in 7 commonly used programming languages (C++, Java, Python, C#, Javascript, PHP, C), and natural language (English).
facebook/flores	facebook	The creation of FLORES-200 doubles the existing language coverage of FLORES-101. Given the nature of the new languages, which have less standardization and require more specialized professional translations, the verification process became more complex. This required modifications to the translation workflow. FLORES-200 has several languages which were not translated from English. Specifically, several languages were translated from Spanish, French, Russian and Modern Standard Arabic. Moreover, FLORES-200 also includes two script alternatives for four languages. FLORES-200 consists of translations from 842 distinct web articles, totaling 3001 sentences. These sentences are divided into three splits: dev, devtest, and test (hidden). On average, sentences are approximately 21 words long.
elihoole/asrs-aviation-reports	elihoole	Dataset Card for ASRS Aviation Incident Reports Dataset Summary This dataset collects 47,723 aviation incident reports published in the Aviation Safety Reporting System (ASRS) database maintained by NASA. Supported Tasks and Leaderboards 'summarization': Dataset can be used to train a model for abstractive and extractive summarization. The model performance is measured by how high the output summary's ROUGE score for a given narrative account of… See the full description on the dataset page: https://huggingface.co/datasets/elihoole/asrs-aviation-reports.
demelin/moral_stories	demelin	Moral Stories is a crowd-sourced dataset of structured, branching narratives for the study of grounded, goal-oriented social reasoning. For detailed information, see https://aclanthology.org/2021.emnlp-main.54.pdf.
rajistics/indian_food_images	rajistics	Source of dataset: Kaggle This Dataset contains different images of food in 20 different classes. Some of the classes are of Indian food. All the images are extracted from google. Images per classes are little so Data augmentation and transfer learning will be best suited here. Classes of the model: "burger", "butter_naan", "chai", "chapati", "chole_bhature", "dal_makhani", "dhokla", "fried_rice", "idli", "jalebi", "kaathi_rolls", "kadai_paneer", "kulfi", "masala_dosa", "momos", "paani_puri"… See the full description on the dataset page: https://huggingface.co/datasets/rajistics/indian_food_images.
tner/mit_movie_trivia	tner	MIT Movie
tner/mit_restaurant	tner	[mit_restaurant NER dataset](https://groups.csail.mit.edu/sls/downloads/)
Muennighoff/xwinograd	Muennighoff	A multilingual collection of Winograd Schemas in six languages that can be used for evaluation of cross-lingual commonsense reasoning capabilities.
deepmind/code_contests	deepmind	Dataset Card for CodeContests Dataset Summary CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of programming problems, from a variety of sources: Site URL Source Aizu https://judge.u-aizu.ac.jp CodeNet AtCoder https://atcoder.jp CodeNet CodeChef https://www.codechef.com description2code Codeforces https://codeforces.com description2code and Codeforces HackerEarth… See the full description on the dataset page: https://huggingface.co/datasets/deepmind/code_contests.
naver-clova-ix/synthdog-ja	naver-clova-ix	Donut 🍩 : OCR-Free Document Understanding Transformer (ECCV 2022) -- SynthDoG datasets For more information, please visit https://github.com/clovaai/donut The links to the SynthDoG-generated datasets are here: synthdog-en: English, 0.5M. synthdog-zh: Chinese, 0.5M. synthdog-ja: Japanese, 0.5M. synthdog-ko: Korean, 0.5M. To generate synthetic datasets with our SynthDoG, please see ./synthdog/README.md and our paper for details. How to Cite If you find this work… See the full description on the dataset page: https://huggingface.co/datasets/naver-clova-ix/synthdog-ja.
joelniklaus/mapa	joelniklaus	Dataset Card for Multilingual European Datasets for Sensitive Entity Detection in the Legal Domain Dataset Summary The dataset consists of 12 documents (9 for Spanish due to parsing errors) taken from EUR-Lex, a multilingual corpus of court decisions and legal dispositions in the 24 official languages of the European Union. The documents have been annotated for named entities following the guidelines of the MAPA project which foresees two annotation level, a… See the full description on the dataset page: https://huggingface.co/datasets/joelniklaus/mapa.
FinanceInc/auditor_sentiment	FinanceInc	Dataset Card for Auditor Sentiment Dataset Description Auditor review sentiment collected by News Department Point of Contact: Talked to COE for Auditing, currently [email protected] Dataset Summary Auditor sentiment dataset of sentences from financial news. The dataset consists of several thousand sentences from English language financial news categorized by sentiment. Supported Tasks and Leaderboards Sentiment Classification… See the full description on the dataset page: https://huggingface.co/datasets/FinanceInc/auditor_sentiment.
Artificio/WikiArt	Artificio	Dataset Card for "WikiArt" More Information needed
ttxy/emotion	ttxy	一个包含六种基本情绪（愤怒、恐惧、喜悦、爱、悲伤和惊讶）的英文Twitter消息数据集 Github 链接 https://github.com/dair-ai/emotion_dataset
joelniklaus/lextreme	joelniklaus	The LEXTREME Benchmark is a collection of multilingual datasets for evaluating model performance across a diverse set of legal NLU tasks.
ziwenyd/transcoder-geeksforgeeks	ziwenyd	statistics cpp-java: 627 pairs python-java: 616 pairs cpp-python: 545 pairs
daekeun-ml/naver-news-summarization-ko	daekeun-ml	This dataset is a custom dataset created by the author by crawling Naver News (https://news.naver.com) for the Korean NLP model hands-on. Period: July 1, 2022 - July 10, 2022 Subject: IT, economics DatasetDict({ train: Dataset({ features: ['date', 'category', 'press', 'title', 'document', 'link', 'summary'], num_rows: 22194 }) test: Dataset({ features: ['date', 'category', 'press', 'title', 'document', 'link', 'summary'], num_rows: 2740 })… See the full description on the dataset page: https://huggingface.co/datasets/daekeun-ml/naver-news-summarization-ko.
Corran/pexelvideos	Corran	Pexel Videos 358,551 video urls, average length 19.5s, and associated metadata from pexels.com. Data was extracted from their video sitemaps (pexels.com/robots.txt) on 01/08/2022. Data is stored in PexelVideos.parquet.gzip as a gzipped parquet To get this data ensure you have git installed and do !git lfs clone https://huggingface.co/datasets/Corran/pexelvideos/ In python the reccomended reading is by opening the file with pandas. !pip install pandas import pandas… See the full description on the dataset page: https://huggingface.co/datasets/Corran/pexelvideos.
owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH	owaiskha9654	This dataset consists of a approx 50k collection of research articles from PubMed repository. Originally these documents are manually annotated by Biomedical Experts with their MeSH labels and each articles are described in terms of 10-15 MeSH labels. In this Dataset we have huge numbers of labels present as a MeSH major which is raising the issue of extremely large output space and severe label sparsity issues. To solve this Issue Dataset has been Processed and mapped to its root as Described… See the full description on the dataset page: https://huggingface.co/datasets/owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH.
Bingsu/laion2B-multi-korean-subset	Bingsu	laion2B-multi-korean-subset About dataset a subset data of laion/laion2B-multi, including only korean Lisence CC-BY-4.0 Data Structure Data Instance >>> from datasets import load_dataset >>> dataset = load_dataset("Bingsu/laion2B-multi-korean-subset") >>> dataset DatasetDict({ train: Dataset({ features: ['SAMPLE_ID', 'URL', 'TEXT', 'HEIGHT', 'WIDTH', 'LICENSE', 'LANGUAGE', 'NSFW', 'similarity']… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/laion2B-multi-korean-subset.
dali-does/clevr-math	dali-does	CLEVR-Math is a dataset for compositional language, visual and mathematical reasoning. CLEVR-Math poses questions about mathematical operations on visual scenes using subtraction and addition, such as "Remove all large red cylinders. How many objects are left?". There are also adversarial (e.g. "Remove all blue cubes. How many cylinders are left?") and multihop questions (e.g. "Remove all blue cubes. Remove all small purple spheres. How many objects are left?").
pcuenq/oxford-pets	pcuenq	Oxford-IIIT Pet Dataset Images from The Oxford-IIIT Pet Dataset. Only images and labels have been pushed, segmentation annotations were ignored. Homepage: https://www.robots.ox.ac.uk/~vgg/data/pets/ License: Same as the original dataset.
scikit-learn/churn-prediction	scikit-learn	Customer churn prediction dataset of a fictional telecommunication company made by IBM Sample Datasets. Context Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs. Content Each row represents a customer, each column contains customer’s attributes described on the column metadata. The data set includes information about: Customers who left within the last month: the column is called Churn Services that each customer… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/churn-prediction.
hoskinson-center/proof-pile	hoskinson-center	A dataset of high quality mathematical text.
SLPL/syntran-fa	SLPL	SynTran-fa Syntactic Transformed Version of Farsi QA datasets to make fluent responses from questions and short answers. You can use this dataset by the code below: import datasets data = datasets.load_dataset('SLPL/syntran-fa', split="train") Dataset Description Homepage: Sharif-SLPL Repository: SynTran-fa Point of Contact: Sadra Sabouri Paper: SynTran-fa: Generating Comprehensive Answers for Farsi QA Pairs via Syntactic Transformation Dataset… See the full description on the dataset page: https://huggingface.co/datasets/SLPL/syntran-fa.
UCL-DARK/ludwig	UCL-DARK	TODO
juletxara/visual-spatial-reasoning	juletxara	The Visual Spatial Reasoning (VSR) corpus is a collection of caption-image pairs with true/false labels. Each caption describes the spatial relation of two individual objects in the image, and a vision-language model (VLM) needs to judge whether the caption is correctly describing the image (True) or not (False).
RUCAIBox/Story-Generation	RUCAIBox	This is the story generation datasets collected by TextBox, including: ROCStories (roc) WritingPrompts (wp) Hippocorpus (hc) WikiPlots (wikip) ChangeMyView (cmv). The detail and leaderboard of each dataset can be found in TextBox page.
Bingsu/zeroth-korean	Bingsu	Zeroth-Korean Zeroth-Korean The data set contains transcriebed audio data for Korean. There are 51.6 hours transcribed Korean audio for training data (22,263 utterances, 105 people, 3000 sentences) and 1.2 hours transcribed Korean audio for testing data (457 utterances, 10 people). This corpus also contains pre-trained/designed language model, lexicon and morpheme-based segmenter(morfessor). Zeroth project introduces free Korean speech corpus and aims to make… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/zeroth-korean.
AhmedSSoliman/CodeXGLUE-CONCODE	AhmedSSoliman	Concode dataset A large dataset with over 100,000 examples consisting of Java classes from online code repositories, and develop a new encoder-decoder architecture that models the interaction between the method documentation and the class environment. Concode dataset is a widely used code generation dataset from Iyer's EMNLP 2018 paper Mapping Language to Code in Programmatic Context. Data statistics of concode dataset are shown in the below table: #Examples Train… See the full description on the dataset page: https://huggingface.co/datasets/AhmedSSoliman/CodeXGLUE-CONCODE.
GateNLP/broad_twitter_corpus	GateNLP	This is the Broad Twitter corpus, a dataset of tweets collected over stratified times, places and social uses. The goal is to represent a broad range of activities, giving a dataset more representative of the language used in this hardest of social media formats to process. Further, the BTC is annotated for named entities. For more details see [https://aclanthology.org/C16-1111/](https://aclanthology.org/C16-1111/)
MLCommons/peoples_speech	MLCommons	Dataset Card for People's Speech Dataset Summary The People's Speech Dataset is among the world's largest English speech recognition corpus today that is licensed for academic and commercial usage under CC-BY-SA and CC-BY 4.0. It includes 30,000+ hours of transcribed speech in English languages with a diverse set of speakers. This open dataset is large enough to train speech-to-text systems and crucially is available with a permissive license.… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/peoples_speech.
allenai/real-toxicity-prompts	allenai	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… See the full description on the dataset page: https://huggingface.co/datasets/allenai/real-toxicity-prompts.
edinburghcstr/ami	edinburghcstr	The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers. \n
ariesutiono/entailment-bank-v3	ariesutiono	Entailment bank dataset This dataset raw source can be found at allenai's Github. If you use this dataset, it is best to cite the original paper @article{entalmentbank2021, title={Explaining Answers with Entailment Trees}, author={Dalvi, Bhavana and Jansen, Peter and Tafjord, Oyvind and Xie, Zhengnan and Smith, Hannah and Pipatanangkura, Leighanna and Clark, Peter}, journal={EMNLP}, year={2021} }
tyqiangz/multilingual-sentiments	tyqiangz	Multilingual Sentiments Dataset A collection of multilingual sentiments datasets grouped into 3 classes -- positive, neutral, negative. Most multilingual sentiment datasets are either 2-class positive or negative, 5-class ratings of products reviews (e.g. Amazon multilingual dataset) or multiple classes of emotions. However, to an average person, sometimes positive, negative and neutral classes suffice and are more straightforward to perceive and annotate. Also, a… See the full description on the dataset page: https://huggingface.co/datasets/tyqiangz/multilingual-sentiments.
masakhane/mafand	masakhane	MAFAND-MT is the largest MT benchmark for African languages in the news domain, covering 21 languages. The languages covered are: - Amharic - Bambara - Ghomala - Ewe - Fon - Hausa - Igbo - Kinyarwanda - Luganda - Luo - Mossi - Nigerian-Pidgin - Chichewa - Shona - Swahili - Setswana - Twi - Wolof - Xhosa - Yoruba - Zulu The train/validation/test sets are available for 16 languages, and validation/test set for amh, kin, nya, sna, and xho For more details see https://aclanthology.org/2022.naacl-main.223/
RCC-MSU/collection3	RCC-MSU	Collection3 is a Russian dataset for named entity recognition annotated with LOC (location), PER (person), and ORG (organization) tags. Dataset is based on collection Persons-1000 originally containing 1000 news documents labeled only with names of persons. Additional labels were added by Valerie Mozharova and Natalia Loukachevitch. Conversion to the IOB2 format and splitting into train, validation and test sets was done by DeepPavlov team. For more details see https://ieeexplore.ieee.org/document/7584769 and http://labinform.ru/pub/named_entities/index.htm
ai-forever/Peter	ai-forever	Digital Peter The Peter dataset can be used for reading texts from the manuscripts written by Peter the Great. The dataset annotation contain end-to-end markup for training detection and OCR models, as well as an end-to-end model for reading text from pages. Paper is available at http://arxiv.org/abs/2103.09354 Description Digital Peter is an educational task with a historical slant created on the basis of several AI technologies (Computer Vision, NLP, and… See the full description on the dataset page: https://huggingface.co/datasets/ai-forever/Peter.
kakaobrain/coyo-700m	kakaobrain	Dataset Card for COYO-700M Dataset Summary COYO-700M is a large-scale dataset that contains 747M image-text pairs as well as many other meta-attributes to increase the usability to train various models. Our dataset follows a similar strategy to previous vision-and-language datasets, collecting many informative pairs of alt-text and its associated image in HTML documents. We expect COYO to be used to train popular large-scale foundation models complementary to… See the full description on the dataset page: https://huggingface.co/datasets/kakaobrain/coyo-700m.
iejMac/CLIP-WebVid	iejMac	version https://git-lfs.github.com/spec/v1 oid sha256:3e0e15fa0c5cc81675bd69af8eb469d128a725c1a7bfc71f03b7877b7b650567 size 21
ShapeNet/ShapeNetSem-archive	ShapeNet	This repository contains archives (zip files) for ShapeNetSem, a subset of ShapeNet richly annotated with physical attributes. Please see DATA.md for details about the data. If you use ShapeNet data, you agree to abide by the ShapeNet terms of use. You are only allowed to redistribute the data to your research associates and colleagues provided that they first agree to be bound by these terms and conditions. If you use this data, please cite the main ShapeNet technical report and the… See the full description on the dataset page: https://huggingface.co/datasets/ShapeNet/ShapeNetSem-archive.
demo-org/diabetes	demo-org	Dataset Card for Auditor_Review This file is a copy, the original version is hosted at data.world
ShapeNet/shapenetcore-glb	ShapeNet	This repository contains ShapeNetCore (v2) in GLB format, a subset of ShapeNet.ShapeNetCore is a densely annotated subset of ShapeNet covering 55 common object categories with ~51,300 unique 3D models. Each model in ShapeNetCore are linked to an appropriate synset in WordNet 3.0. If you use ShapeNet data, you agree to abide by the ShapeNet terms of use. You are only allowed to redistribute the data to your research associates and colleagues provided that they first agree to be bound by… See the full description on the dataset page: https://huggingface.co/datasets/ShapeNet/shapenetcore-glb.
indonesian-nlp/librivox-indonesia	indonesian-nlp	Dataset Card for LibriVox Indonesia 1.0 Dataset Summary The LibriVox Indonesia dataset consists of MP3 audio and a corresponding text file we generated from the public domain audiobooks LibriVox. We collected only languages in Indonesia for this dataset. The original LibriVox audiobooks or sound files' duration varies from a few minutes to a few hours. Each audio file in the speech dataset now lasts from a few seconds to a maximum of 20 seconds. We converted… See the full description on the dataset page: https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia.
bigbio/biosses	bigbio	BIOSSES computes similarity of biomedical sentences by utilizing WordNet as the general domain ontology and UMLS as the biomedical domain specific ontology. The original paper outlines the approaches with respect to using annotator score as golden standard. Source view will return all annotator score individually whereas the Bigbio view will return the mean of the annotator score.
zeroshot/twitter-financial-news-topic	zeroshot	Dataset Description The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their topic. The dataset holds 21,107 documents annotated with 20 labels: topics = { "LABEL_0": "Analyst Update", "LABEL_1": "Fed \| Central Banks", "LABEL_2": "Company \| Product News", "LABEL_3": "Treasuries \| Corporate Debt", "LABEL_4": "Dividend"… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-topic.
jonathanli/law-stack-exchange	jonathanli	Dataset Card for Law Stack Exchange Dataset Dataset Summary Dataset from the Law Stack Exchange, as used in "Parameter-Efficient Legal Domain Adaptation". Citation Information @inproceedings{li-etal-2022-parameter, title = "Parameter-Efficient Legal Domain Adaptation", author = "Li, Jonathan and Bhambhoria, Rohan and Zhu, Xiaodan", booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022", month =… See the full description on the dataset page: https://huggingface.co/datasets/jonathanli/law-stack-exchange.
ai-forever/school_notebooks_RU	ai-forever	School Notebooks Dataset The images of school notebooks with handwritten notes in Russian. The dataset annotation contain end-to-end markup for training detection and OCR models, as well as an end-to-end model for reading text from pages. Annotation format The annotation is in COCO format. The annotation.json should have the following dictionaries: annotation["categories"] - a list of dicts with a categories info (categotiy names and indexes).… See the full description on the dataset page: https://huggingface.co/datasets/ai-forever/school_notebooks_RU.
pysentimiento/spanish-tweets	pysentimiento	spanish-tweets A big corpus of tweets for pretraining embeddings and language models Dataset Summary A big dataset of (mostly) Spanish tweets for pre-training language models (or other representations). Supported Tasks and Leaderboards Language Modeling Languages Mostly Spanish, but some Portuguese, English, and other languages. Dataset Structure Data Fields tweet_id: id of the tweet… See the full description on the dataset page: https://huggingface.co/datasets/pysentimiento/spanish-tweets.
cannlytics/cannabis_results	cannlytics	Cannabis results is a dataset of curated cannabis lab test results. The dataset consists of sub-datasets for each state with any public cannabis lab tests, as well as a sub-dataset that includes all results.
opentargets/clinical_trial_reason_to_stop	opentargets	Dataset Card for Clinical Trials's Reason to Stop Dataset Summary This dataset contains a curated classification of more than 5000 reasons why a clinical trial has suffered an early stop. The text has been extracted from clinicaltrials.gov, the largest resource of clinical trial information. The text has been curated by members of the Open Targets organisation, a project aimed at providing data relevant to drug development. All 17 possible classes have been… See the full description on the dataset page: https://huggingface.co/datasets/opentargets/clinical_trial_reason_to_stop.
dclure/laion-aesthetics-12m-umap	dclure	LAION-Aesthetics :: CLIP → UMAP This dataset is a CLIP (text) → UMAP embedding of the LAION-Aesthetics dataset - specifically the improved_aesthetics_6plus version, which filters the full dataset to images with scores of > 6 under the "aesthetic" filtering model. Thanks LAION for this amazing corpus! The dataset here includes coordinates for 3x separate UMAP fits using different values for the n_neighbors parameter - 10, 30, and 60 - which are broken out as separate columns… See the full description on the dataset page: https://huggingface.co/datasets/dclure/laion-aesthetics-12m-umap.
lambdalabs/pokemon-blip-captions	lambdalabs	Notice of DMCA Takedown Action We have received a DMCA takedown notice from The Pokémon Company International, Inc. In response to this action, we have taken down the dataset. We appreciate your understanding.
Bingsu/openwebtext_20p	Bingsu	openwebtext_20p first 20% of openwebtext

s-nlp/paradetox

s-nlp

ParaDetox: Text Detoxification with Parallel Data (English) This repository contains information about ParaDetox dataset -- the first parallel corpus for the detoxification task -- as well as models and evaluation methodology for the detoxification of English texts. The original paper "ParaDetox: Detoxification with Parallel Data" was presented at ACL 2022 main conference. 📰 Updates [2024] We have also created versions of ParaDetox in more languages. You can checkout a… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/paradetox.

NLPC-UOM/sentence_alignment_dataset-Sinhala-Tamil-English

NLPC-UOM

Dataset summary This is a gold-standard benchmark dataset for sentence alignment, between Sinhala-English-Tamil languages. Data had been crawled from the following news websites. The aligned documents annotated in the dataset NLPC-UOM/document_alignment_dataset-Sinhala-Tamil-English had been considered to annotate the aligned sentences. News Source url Army https://www.army.lk/ Hiru http://www.hirunews.lk ITN https://www.newsfirst.lk Newsfirst… See the full description on the dataset page: https://huggingface.co/datasets/NLPC-UOM/sentence_alignment_dataset-Sinhala-Tamil-English.

mteb/amazon_reviews_multi

mteb

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language. For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long. Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

sileod/movie_recommendation

sileod

Movie recommendation task based on the Movielens dataset

ganchengguang/resume_seven_class

ganchengguang

This is a resume sentence classification dataset constructed based on resume text.（https://www.kaggle.com/datasets/oo7kartik/resume-text-batch）The dataset have seven category.(experience education knowledge project others ) And three element label(header content meta).Because the dataset is a published paper, if you want to use this dataset in a paper or work, please cite following paper.https://arxiv.org/abs/2208.03219 And dataset use in article https://arxiv.org/abs/2209.09450

mteb/sts22-crosslingual-sts

mteb

Scores in this dataset have been inverted to be from least to most similar! The scores in the original STS22 task were from most to least similar. Updates: 2024/07/06: Removed pairs where one of the sentences is empty.

LTCB/enwik8

LTCB

The dataset is based on the Hutter Prize (http://prize.hutter1.net) and contains the first 10^8 bytes of English Wikipedia in 2006 in XML

lmqg/qg_koquad

lmqg

[KorQuAD](https://huggingface.co/datasets/squad_kor_v1) dataset for question generation (QG) task.

BeIR/msmarco

BeIR

Dataset Card for BEIR Benchmark Dataset Summary BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks: Fact-checking: FEVER, Climate-FEVER, SciFact Question-Answering: NQ, HotpotQA, FiQA-2018 Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus News Retrieval: TREC-NEWS, Robust04 Argument Retrieval: Touche-2020, ArguAna Duplicate Question Retrieval: Quora, CqaDupstack Citation-Prediction: SCIDOCS Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/msmarco.

Adapting/empathetic_dialogues_v2

Adapting

Fine-tuned empathetic dialogue datasets from https://huggingface.co/datasets/empathetic_dialogues With labeled chat history, system response, question or not and behavior.

AhmedSSabir/Japanese-wiki-dump-sentence-dataset

AhmedSSabir

Dataset 5M (5121625) clean Japanese full sentence with the context. This dataset can be used to learn unsupervised semantic similarity, etc.

truthfulqa/truthful_qa

truthfulqa

Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.

google/bigbench

google

The Beyond the Imitation Game Benchmark (BIG-bench) is a collaborative benchmark intended to probe large language models, and extrapolate their future capabilities.

Bingsu/Human_Action_Recognition

Bingsu

Dataset Summary A dataset from kaggle. origin: https://dphi.tech/challenges/data-sprint-76-human-activity-recognition/233/data Introduction The dataset features 15 different classes of Human Activities. The dataset contains about 12k+ labelled images including the validation images. Each image has only one human activity category and are saved in separate folders of the labelled classes PROBLEM STATEMENT Human Action Recognition (HAR) aims to… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/Human_Action_Recognition.

google/quickdraw

google

The Quick Draw Dataset is a collection of 50 million drawings across 345 categories, contributed by players of the game Quick, Draw!. The drawings were captured as timestamped vectors, tagged with metadata including what the player was asked to draw and in which country the player was located.

sil-ai/bloom-speech

sil-ai

Bloom-speech is a dataset of text aligned speech from bloomlibrary.org. This dataset contains over 50 languages including many low-resource languages. This dataset should be useful for training and/or testing speech-to-text or text-to-speech/ASR models.

speechcolab/gigaspeech

speechcolab

GigaSpeech is an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training, and 40,000 hours of total audio suitable for semi-supervised and unsupervised training. Around 40,000 hours of transcribed audio is first collected from audiobooks, podcasts and YouTube, covering both read and spontaneous speaking styles, and a variety of topics, such as arts, science, sports, etc. A new forced alignment and segmentation pipeline is proposed to create sentence segments suitable for speech recognition training, and to filter out segments with low-quality transcription. For system training, GigaSpeech provides five subsets of different sizes, 10h, 250h, 1000h, 2500h, and 10000h. For our 10,000-hour XL training subset, we cap the word error rate at 4% during the filtering/validation stage, and for all our other smaller training subsets, we cap it at 0%. The DEV and TEST evaluation sets, on the other hand, are re-processed by professional human transcribers to ensure high transcription quality.

SetFit/CR

SetFit

Customer Reviews This dataset is a port of the official CR dataset from this paper. There is no validation split.

demo-org/auditor_review

demo-org

Dataset Card for Auditor_Review Dataset Description Auditor review data collected by News Department Point of Contact: Talked to COE for Auditing, currently [email protected] Dataset Summary Auditor sentiment dataset of sentences from financial news. The dataset consists of 3500 sentences from English language financial news categorized by sentiment. The dataset is divided by the agreement rate of 5-8 annotators. Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/demo-org/auditor_review.

thu-coai/lccc

thu-coai

LCCC: Large-scale Cleaned Chinese Conversation corpus (LCCC) is a large corpus of Chinese conversations. A rigorous data cleaning pipeline is designed to ensure the quality of the corpus. This pipeline involves a set of rules and several classifier-based filters. Noises such as offensive or sensitive words, special symbols, emojis, grammatically incorrect sentences, and incoherent conversations are filtered.

julien-c/kaggle-hugomathien-soccer

julien-c

Source: https://www.kaggle.com/datasets/hugomathien/soccer by Hugo Mathien About Dataset The ultimate Soccer database for data analysis and machine learning What you get: +25,000 matches +10,000 players 11 European Countries with their lead championship Seasons 2008 to 2016 Players and Teams' attributes* sourced from EA Sports' FIFA video game series, including the weekly updates Team line up with squad formation (X, Y coordinates) Betting odds from up to 10… See the full description on the dataset page: https://huggingface.co/datasets/julien-c/kaggle-hugomathien-soccer.

valurank/Adult-content-dataset

valurank

Dataset Card for Adult_Content_Detection Dataset Description 850 Articles descriptions classified into two different categories namely: Adult, and Non_Adult Languages The text in the dataset is in English Dataset Structure The dataset consists of two columns namely Description and Category. The Description column consists of the overview of the article and the Category column consists of the class each article belongs to… See the full description on the dataset page: https://huggingface.co/datasets/valurank/Adult-content-dataset.

mounikaiiith/Telugu-Sarcasm

mounikaiiith

Do cite the below references for using the dataset: @article{marreddy2022resource, title={Am I a Resource-Poor Language? Data Sets, Embeddings, Models and Analysis for four different NLP tasks in Telugu Language}, author={Marreddy, Mounika and Oota, Subba Reddy and Vakada, Lakshmi Sireesha and Chinni, Venkata Charan and Mamidi, Radhika}, journal={Transactions on Asian and Low-Resource Language Information Processing}, publisher={ACM New York, NY} } @article{marreddy2022multi… See the full description on the dataset page: https://huggingface.co/datasets/mounikaiiith/Telugu-Sarcasm.

HuggingFaceM4/Stanford-Cars

HuggingFaceM4

Code snippet to visualise the position of the box import matplotlib.image as img import matplotlib.pyplot as plt from datasets import load_dataset from matplotlib.patches import Rectangle # Load dataset ds_name = "SaulLu/Stanford-Cars" ds = load_dataset(ds_name, use_auth_token=True) # Extract information for the sample we want to show index = 100 sample = ds["train"][index] box_coord = sample["bbox"][0] img_path = sample["image"].filename # Create plot # define Matplotlib figure… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceM4/Stanford-Cars.

Shayanvsf/pquad_public

Shayanvsf

\\\ParSQuAD: Persian Question Answering Dataset based on Machine Translation of SQuAD 2.0

Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder

Nexdata

Dataset Card for Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder Dataset Summary 995 local Cantonese speakers participated in the recording, and conducted face-to-face communication in a natural way. They had free discussion on a number of given topics, with a wide range of fields; the voice was natural and fluent, in line with the actual dialogue scene. Text is transferred manually, with high accuracy. For more details, please… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Cantonese_Conversational_Speech_Data_by_Mobile_Phone_and_Voice_Recorder.

iejMac/CLIP-Kinetics700

iejMac

Dataset Card for CLIP-Kinetics70 Dataset Description Dataset Summary CLIP-Kinetics700 is a compressed version of the Kinetics700 dataset using OpenAI's CLIP model. The original dataset is ~700 GB making it difficult to use and hold in memory on one machine. By downsampling each video to 1 FPS and encoding the frames using CLIP we we're able to compress the dataset to ~8 GB making it very memory-friendly and easy to use. Dataset… See the full description on the dataset page: https://huggingface.co/datasets/iejMac/CLIP-Kinetics700.

Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array

Nexdata

Dataset Card for Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array Dataset Summary The data consists of multiple sets of products, each with a different type of microphone arrays. Noise data is collected from real home scenes of the indoor residence of ordinary residents. The data set can be used for tasks such as voice enhancement and automatic speech recognition in a home scene. For more details, please refer to the link:… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array.

Nexdata/Emotional_Video_Data

Nexdata

Dataset Card for Nexdata/Emotional_Video_Data Dataset Summary 1,003 People - Emotional Video Data. The data diversity includes multiple races, multiple indoor scenes, multiple age groups, multiple languages, multiple emotions (11 types of facial emotions, 15 types of inner emotions). For each sentence in each video, emotion types (including facial emotions and inner emotions), start & end time, and text transcription were annotated.This dataset can be used for… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Emotional_Video_Data.

nateraw/parti-prompts

nateraw

Dataset Card for PartiPrompts (P2) Dataset Summary PartiPrompts (P2) is a rich set of over 1600 prompts in English that we release as part of this work. P2 can be used to measure model capabilities across various categories and challenge aspects. P2 prompts can be simple, allowing us to gauge the progress from scaling. They can also be complex, such as the following 67-word description we created for Vincent van Gogh’s The Starry Night (1889): Oil-on-canvas… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/parti-prompts.

CShorten/ML-ArXiv-Papers

CShorten

This dataset contains the subset of ArXiv papers with the "cs.LG" tag to indicate the paper is about Machine Learning. The core dataset is filtered from the full ArXiv dataset hosted on Kaggle: https://www.kaggle.com/datasets/Cornell-University/arxiv. The original dataset contains roughly 2 million papers. This dataset contains roughly 100,000 papers following the category filtering. The dataset is maintained by with requests to the ArXiv API. The current iteration of the dataset only contains… See the full description on the dataset page: https://huggingface.co/datasets/CShorten/ML-ArXiv-Papers.

fever/feverous

fever

Dataset Card for FEVEROUS Dataset Summary With billions of individual pages on the web providing information on almost every conceivable topic, we should have the ability to collect facts that answer almost every conceivable question. However, only a small fraction of this information is contained in structured sources (Wikidata, Freebase, etc.) – we are therefore limited by our ability to transform free-form text to structured knowledge. There is, however… See the full description on the dataset page: https://huggingface.co/datasets/fever/feverous.

stanfordnlp/concurrentqa

stanfordnlp

ConcurrentQA is a textual multi-hop QA benchmark to require concurrent retrieval over multiple data-distributions (i.e. Wikipedia and email data). This dataset was constructed by researchers at Stanford and FAIR, following the data collection process and schema of HotpotQA. This benchmark can be used to study generalization in retrieval as well as privacy when reasoning across multiple privacy scopes --- i.e. public Wikipedia documents and private emails. This dataset is for the… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/concurrentqa.

joelniklaus/brazilian_court_decisions

joelniklaus

Dataset Card for predicting-brazilian-court-decisions Dataset Summary The dataset is a collection of 4043 Ementa (summary) court decisions and their metadata from the Tribunal de Justiça de Alagoas (TJAL, the State Supreme Court of Alagoas (Brazil). The court decisions are labeled according to 7 categories and whether the decisions were unanimous on the part of the judges or not. The dataset supports the task of Legal Judgment Prediction. Supported… See the full description on the dataset page: https://huggingface.co/datasets/joelniklaus/brazilian_court_decisions.

rkstgr/mtg-jamendo

rkstgr

Repackaging of the MTG Jamendo dataset. We present the MTG-Jamendo Dataset, a new open dataset for music auto-tagging. It is built using music available at Jamendo under Creative Commons licenses and tags provided by content creators. The dataset contains over 55,000 full audio tracks with 195 tags from genre, instrument, and mood/theme categories.

HuggingFaceM4/VQAv2

HuggingFaceM4

VQA is a new dataset containing open-ended questions about images. These questions require an understanding of vision, language and commonsense knowledge to answer.

codeparrot/codecomplex

codeparrot

CodeComplex Dataset Dataset Description CodeComplex consists of 4,200 Java codes submitted to programming competitions by human programmers and their complexity labels annotated by a group of algorithm experts. How to use it You can load and iterate through the dataset with the following two lines of code: from datasets import load_dataset ds = load_dataset("codeparrot/codecomplex", split="train") print(next(iter(ds))) Data Structure… See the full description on the dataset page: https://huggingface.co/datasets/codeparrot/codecomplex.

Nexdata/Human_Facial_Skin_Defects_Data

Nexdata

Dataset Card for Nexdata/Human_Facial_Skin_Defects_Data Dataset Summary 4,788 Chinese people 5,105 images Human Facial Skin Defects Data. The data includes the following five types of facial skin defects: acne, acne marks, stains, wrinkles and dark circles. This data can be used for tasks such as skin defects detection. For more details, please refer to the link: https://www.nexdata.ai/datasets/computervision/1052?source=Huggingface Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata/Human_Facial_Skin_Defects_Data.

launch/open_question_type

launch

Open-ended question type annotated dataset.

knkarthick/samsum

knkarthick

Dataset Card for SAMSum Corpus Dataset Description Links Homepage: hhttps://arxiv.org/abs/1911.12237v2 Repository: https://arxiv.org/abs/1911.12237v2 Paper: https://arxiv.org/abs/1911.12237v2 Point of Contact: https://huggingface.co/knkarthick Dataset Summary The SAMSum dataset contains about 16k messenger-like conversations with summaries. Conversations were created and written down by linguists fluent in English. Linguists were… See the full description on the dataset page: https://huggingface.co/datasets/knkarthick/samsum.

kensho/spgispeech

kensho

The SPGISpeech corpus is derived from company earnings calls manually transcribed by S&P Global, Inc. according to a pro- fessional style guide detailing conventions for capitalization, punctuation, denormalization of non-standard words and tran- scription of disfluencies in spontaneous speech. The basic unit of SPGISpeech is a pair consisting of a 5 to 15 second long 16 bit, 16kHz mono wav audio file and its transcription..

codeparrot/github-code-clean

codeparrot

The GitHub Code clean dataset in a more filtered version of codeparrot/github-code dataset, it consists of 115M code files from GitHub in 32 programming languages with 60 extensions totaling in almost 1TB of text data.

zh-plus/tiny-imagenet

zh-plus

Dataset Card for tiny-imagenet Dataset Summary Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images. Languages The class labels in the dataset are in English. Dataset Structure Data Instances { 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190… See the full description on the dataset page: https://huggingface.co/datasets/zh-plus/tiny-imagenet.

benschill/brain-tumor-collection

benschill

This dataset is intended as a test case for classification tasks (4 different kinds of brain xrays). The dataset consists of almost 1400 JPEG images grouped into two splits - training and validation. Each split contains 4 categories labeled as n0~n3, each corresponding to a cancer result of the mrt. | Label | Xray Category | Train Images | Validation Images | | ----- | --------------------- | ------------ | ----------------- | | n0 | glioma_tumor | 826 | 100 | | n1 | meningioma_tumor | 822 | 115 | | n2 | pituitary_tumor | 827 | 74 | | n3 | no_tumor | 395 | 105 |

nreimers/reddit_question_best_answers

nreimers

Question & question body together with the best answers to that question from Reddit. The score for the question / answer is the upvote count (i.e. positive-negative upvotes). Only questions / answers that have these properties were extracted: min_score = 3 min_title_len = 20 min_body_len = 100

codeparrot/xlcost-text-to-code

codeparrot

XLCoST is a machine learning benchmark dataset that contains fine-grained parallel data in 7 commonly used programming languages (C++, Java, Python, C#, Javascript, PHP, C), and natural language (English).

facebook/flores

facebook

The creation of FLORES-200 doubles the existing language coverage of FLORES-101. Given the nature of the new languages, which have less standardization and require more specialized professional translations, the verification process became more complex. This required modifications to the translation workflow. FLORES-200 has several languages which were not translated from English. Specifically, several languages were translated from Spanish, French, Russian and Modern Standard Arabic. Moreover, FLORES-200 also includes two script alternatives for four languages. FLORES-200 consists of translations from 842 distinct web articles, totaling 3001 sentences. These sentences are divided into three splits: dev, devtest, and test (hidden). On average, sentences are approximately 21 words long.

elihoole/asrs-aviation-reports

elihoole

Dataset Card for ASRS Aviation Incident Reports Dataset Summary This dataset collects 47,723 aviation incident reports published in the Aviation Safety Reporting System (ASRS) database maintained by NASA. Supported Tasks and Leaderboards 'summarization': Dataset can be used to train a model for abstractive and extractive summarization. The model performance is measured by how high the output summary's ROUGE score for a given narrative account of… See the full description on the dataset page: https://huggingface.co/datasets/elihoole/asrs-aviation-reports.

demelin/moral_stories

demelin

Moral Stories is a crowd-sourced dataset of structured, branching narratives for the study of grounded, goal-oriented social reasoning. For detailed information, see https://aclanthology.org/2021.emnlp-main.54.pdf.

rajistics/indian_food_images

rajistics

Source of dataset: Kaggle This Dataset contains different images of food in 20 different classes. Some of the classes are of Indian food. All the images are extracted from google. Images per classes are little so Data augmentation and transfer learning will be best suited here. Classes of the model: "burger", "butter_naan", "chai", "chapati", "chole_bhature", "dal_makhani", "dhokla", "fried_rice", "idli", "jalebi", "kaathi_rolls", "kadai_paneer", "kulfi", "masala_dosa", "momos", "paani_puri"… See the full description on the dataset page: https://huggingface.co/datasets/rajistics/indian_food_images.

tner/mit_movie_trivia

tner

MIT Movie

tner/mit_restaurant

tner

[mit_restaurant NER dataset](https://groups.csail.mit.edu/sls/downloads/)

Muennighoff/xwinograd

Muennighoff

A multilingual collection of Winograd Schemas in six languages that can be used for evaluation of cross-lingual commonsense reasoning capabilities.

deepmind/code_contests

deepmind

Dataset Card for CodeContests Dataset Summary CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of programming problems, from a variety of sources: Site URL Source Aizu https://judge.u-aizu.ac.jp CodeNet AtCoder https://atcoder.jp CodeNet CodeChef https://www.codechef.com description2code Codeforces https://codeforces.com description2code and Codeforces HackerEarth… See the full description on the dataset page: https://huggingface.co/datasets/deepmind/code_contests.

naver-clova-ix/synthdog-ja

naver-clova-ix

Donut 🍩 : OCR-Free Document Understanding Transformer (ECCV 2022) -- SynthDoG datasets For more information, please visit https://github.com/clovaai/donut The links to the SynthDoG-generated datasets are here: synthdog-en: English, 0.5M. synthdog-zh: Chinese, 0.5M. synthdog-ja: Japanese, 0.5M. synthdog-ko: Korean, 0.5M. To generate synthetic datasets with our SynthDoG, please see ./synthdog/README.md and our paper for details. How to Cite If you find this work… See the full description on the dataset page: https://huggingface.co/datasets/naver-clova-ix/synthdog-ja.

joelniklaus/mapa

joelniklaus

Dataset Card for Multilingual European Datasets for Sensitive Entity Detection in the Legal Domain Dataset Summary The dataset consists of 12 documents (9 for Spanish due to parsing errors) taken from EUR-Lex, a multilingual corpus of court decisions and legal dispositions in the 24 official languages of the European Union. The documents have been annotated for named entities following the guidelines of the MAPA project which foresees two annotation level, a… See the full description on the dataset page: https://huggingface.co/datasets/joelniklaus/mapa.

FinanceInc/auditor_sentiment

FinanceInc

Dataset Card for Auditor Sentiment Dataset Description Auditor review sentiment collected by News Department Point of Contact: Talked to COE for Auditing, currently [email protected] Dataset Summary Auditor sentiment dataset of sentences from financial news. The dataset consists of several thousand sentences from English language financial news categorized by sentiment. Supported Tasks and Leaderboards Sentiment Classification… See the full description on the dataset page: https://huggingface.co/datasets/FinanceInc/auditor_sentiment.

Artificio/WikiArt

Artificio

Dataset Card for "WikiArt" More Information needed

ttxy/emotion

ttxy

一个包含六种基本情绪（愤怒、恐惧、喜悦、爱、悲伤和惊讶）的英文Twitter消息数据集 Github 链接 https://github.com/dair-ai/emotion_dataset

joelniklaus/lextreme

joelniklaus

The LEXTREME Benchmark is a collection of multilingual datasets for evaluating model performance across a diverse set of legal NLU tasks.

ziwenyd/transcoder-geeksforgeeks

ziwenyd

statistics cpp-java: 627 pairs python-java: 616 pairs cpp-python: 545 pairs

daekeun-ml/naver-news-summarization-ko

daekeun-ml

This dataset is a custom dataset created by the author by crawling Naver News (https://news.naver.com) for the Korean NLP model hands-on. Period: July 1, 2022 - July 10, 2022 Subject: IT, economics DatasetDict({ train: Dataset({ features: ['date', 'category', 'press', 'title', 'document', 'link', 'summary'], num_rows: 22194 }) test: Dataset({ features: ['date', 'category', 'press', 'title', 'document', 'link', 'summary'], num_rows: 2740 })… See the full description on the dataset page: https://huggingface.co/datasets/daekeun-ml/naver-news-summarization-ko.

Corran/pexelvideos

Corran

Pexel Videos 358,551 video urls, average length 19.5s, and associated metadata from pexels.com. Data was extracted from their video sitemaps (pexels.com/robots.txt) on 01/08/2022. Data is stored in PexelVideos.parquet.gzip as a gzipped parquet To get this data ensure you have git installed and do !git lfs clone https://huggingface.co/datasets/Corran/pexelvideos/ In python the reccomended reading is by opening the file with pandas. !pip install pandas import pandas… See the full description on the dataset page: https://huggingface.co/datasets/Corran/pexelvideos.

owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH

owaiskha9654

This dataset consists of a approx 50k collection of research articles from PubMed repository. Originally these documents are manually annotated by Biomedical Experts with their MeSH labels and each articles are described in terms of 10-15 MeSH labels. In this Dataset we have huge numbers of labels present as a MeSH major which is raising the issue of extremely large output space and severe label sparsity issues. To solve this Issue Dataset has been Processed and mapped to its root as Described… See the full description on the dataset page: https://huggingface.co/datasets/owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH.

Bingsu/laion2B-multi-korean-subset

Bingsu

laion2B-multi-korean-subset About dataset a subset data of laion/laion2B-multi, including only korean Lisence CC-BY-4.0 Data Structure Data Instance >>> from datasets import load_dataset >>> dataset = load_dataset("Bingsu/laion2B-multi-korean-subset") >>> dataset DatasetDict({ train: Dataset({ features: ['SAMPLE_ID', 'URL', 'TEXT', 'HEIGHT', 'WIDTH', 'LICENSE', 'LANGUAGE', 'NSFW', 'similarity']… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/laion2B-multi-korean-subset.

dali-does/clevr-math

dali-does

CLEVR-Math is a dataset for compositional language, visual and mathematical reasoning. CLEVR-Math poses questions about mathematical operations on visual scenes using subtraction and addition, such as "Remove all large red cylinders. How many objects are left?". There are also adversarial (e.g. "Remove all blue cubes. How many cylinders are left?") and multihop questions (e.g. "Remove all blue cubes. Remove all small purple spheres. How many objects are left?").

pcuenq/oxford-pets

pcuenq

Oxford-IIIT Pet Dataset Images from The Oxford-IIIT Pet Dataset. Only images and labels have been pushed, segmentation annotations were ignored. Homepage: https://www.robots.ox.ac.uk/~vgg/data/pets/ License: Same as the original dataset.

scikit-learn/churn-prediction

scikit-learn

Customer churn prediction dataset of a fictional telecommunication company made by IBM Sample Datasets. Context Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs. Content Each row represents a customer, each column contains customer’s attributes described on the column metadata. The data set includes information about: Customers who left within the last month: the column is called Churn Services that each customer… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/churn-prediction.

hoskinson-center/proof-pile

hoskinson-center

A dataset of high quality mathematical text.

SLPL/syntran-fa

SLPL

SynTran-fa Syntactic Transformed Version of Farsi QA datasets to make fluent responses from questions and short answers. You can use this dataset by the code below: import datasets data = datasets.load_dataset('SLPL/syntran-fa', split="train") Dataset Description Homepage: Sharif-SLPL Repository: SynTran-fa Point of Contact: Sadra Sabouri Paper: SynTran-fa: Generating Comprehensive Answers for Farsi QA Pairs via Syntactic Transformation Dataset… See the full description on the dataset page: https://huggingface.co/datasets/SLPL/syntran-fa.

UCL-DARK/ludwig

UCL-DARK

TODO

juletxara/visual-spatial-reasoning

juletxara

The Visual Spatial Reasoning (VSR) corpus is a collection of caption-image pairs with true/false labels. Each caption describes the spatial relation of two individual objects in the image, and a vision-language model (VLM) needs to judge whether the caption is correctly describing the image (True) or not (False).

RUCAIBox/Story-Generation

RUCAIBox

This is the story generation datasets collected by TextBox, including: ROCStories (roc) WritingPrompts (wp) Hippocorpus (hc) WikiPlots (wikip) ChangeMyView (cmv). The detail and leaderboard of each dataset can be found in TextBox page.

Bingsu/zeroth-korean

Bingsu

Zeroth-Korean Zeroth-Korean The data set contains transcriebed audio data for Korean. There are 51.6 hours transcribed Korean audio for training data (22,263 utterances, 105 people, 3000 sentences) and 1.2 hours transcribed Korean audio for testing data (457 utterances, 10 people). This corpus also contains pre-trained/designed language model, lexicon and morpheme-based segmenter(morfessor). Zeroth project introduces free Korean speech corpus and aims to make… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/zeroth-korean.

AhmedSSoliman/CodeXGLUE-CONCODE

AhmedSSoliman

Concode dataset A large dataset with over 100,000 examples consisting of Java classes from online code repositories, and develop a new encoder-decoder architecture that models the interaction between the method documentation and the class environment. Concode dataset is a widely used code generation dataset from Iyer's EMNLP 2018 paper Mapping Language to Code in Programmatic Context. Data statistics of concode dataset are shown in the below table: #Examples Train… See the full description on the dataset page: https://huggingface.co/datasets/AhmedSSoliman/CodeXGLUE-CONCODE.

GateNLP/broad_twitter_corpus

GateNLP

This is the Broad Twitter corpus, a dataset of tweets collected over stratified times, places and social uses. The goal is to represent a broad range of activities, giving a dataset more representative of the language used in this hardest of social media formats to process. Further, the BTC is annotated for named entities. For more details see [https://aclanthology.org/C16-1111/](https://aclanthology.org/C16-1111/)

MLCommons/peoples_speech

MLCommons

Dataset Card for People's Speech Dataset Summary The People's Speech Dataset is among the world's largest English speech recognition corpus today that is licensed for academic and commercial usage under CC-BY-SA and CC-BY 4.0. It includes 30,000+ hours of transcribed speech in English languages with a diverse set of speakers. This open dataset is large enough to train speech-to-text systems and crucially is available with a permissive license.… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/peoples_speech.

allenai/real-toxicity-prompts

allenai

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… See the full description on the dataset page: https://huggingface.co/datasets/allenai/real-toxicity-prompts.

edinburghcstr/ami

edinburghcstr

The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers. \n

ariesutiono/entailment-bank-v3

ariesutiono

Entailment bank dataset This dataset raw source can be found at allenai's Github. If you use this dataset, it is best to cite the original paper @article{entalmentbank2021, title={Explaining Answers with Entailment Trees}, author={Dalvi, Bhavana and Jansen, Peter and Tafjord, Oyvind and Xie, Zhengnan and Smith, Hannah and Pipatanangkura, Leighanna and Clark, Peter}, journal={EMNLP}, year={2021} }

tyqiangz/multilingual-sentiments

tyqiangz

Multilingual Sentiments Dataset A collection of multilingual sentiments datasets grouped into 3 classes -- positive, neutral, negative. Most multilingual sentiment datasets are either 2-class positive or negative, 5-class ratings of products reviews (e.g. Amazon multilingual dataset) or multiple classes of emotions. However, to an average person, sometimes positive, negative and neutral classes suffice and are more straightforward to perceive and annotate. Also, a… See the full description on the dataset page: https://huggingface.co/datasets/tyqiangz/multilingual-sentiments.

masakhane/mafand

masakhane

MAFAND-MT is the largest MT benchmark for African languages in the news domain, covering 21 languages. The languages covered are: - Amharic - Bambara - Ghomala - Ewe - Fon - Hausa - Igbo - Kinyarwanda - Luganda - Luo - Mossi - Nigerian-Pidgin - Chichewa - Shona - Swahili - Setswana - Twi - Wolof - Xhosa - Yoruba - Zulu The train/validation/test sets are available for 16 languages, and validation/test set for amh, kin, nya, sna, and xho For more details see https://aclanthology.org/2022.naacl-main.223/

RCC-MSU/collection3

RCC-MSU

Collection3 is a Russian dataset for named entity recognition annotated with LOC (location), PER (person), and ORG (organization) tags. Dataset is based on collection Persons-1000 originally containing 1000 news documents labeled only with names of persons. Additional labels were added by Valerie Mozharova and Natalia Loukachevitch. Conversion to the IOB2 format and splitting into train, validation and test sets was done by DeepPavlov team. For more details see https://ieeexplore.ieee.org/document/7584769 and http://labinform.ru/pub/named_entities/index.htm

ai-forever/Peter

ai-forever

Digital Peter The Peter dataset can be used for reading texts from the manuscripts written by Peter the Great. The dataset annotation contain end-to-end markup for training detection and OCR models, as well as an end-to-end model for reading text from pages. Paper is available at http://arxiv.org/abs/2103.09354 Description Digital Peter is an educational task with a historical slant created on the basis of several AI technologies (Computer Vision, NLP, and… See the full description on the dataset page: https://huggingface.co/datasets/ai-forever/Peter.

kakaobrain/coyo-700m

kakaobrain

Dataset Card for COYO-700M Dataset Summary COYO-700M is a large-scale dataset that contains 747M image-text pairs as well as many other meta-attributes to increase the usability to train various models. Our dataset follows a similar strategy to previous vision-and-language datasets, collecting many informative pairs of alt-text and its associated image in HTML documents. We expect COYO to be used to train popular large-scale foundation models complementary to… See the full description on the dataset page: https://huggingface.co/datasets/kakaobrain/coyo-700m.

iejMac/CLIP-WebVid

iejMac

version https://git-lfs.github.com/spec/v1 oid sha256:3e0e15fa0c5cc81675bd69af8eb469d128a725c1a7bfc71f03b7877b7b650567 size 21

ShapeNet/ShapeNetSem-archive

ShapeNet

This repository contains archives (zip files) for ShapeNetSem, a subset of ShapeNet richly annotated with physical attributes. Please see DATA.md for details about the data. If you use ShapeNet data, you agree to abide by the ShapeNet terms of use. You are only allowed to redistribute the data to your research associates and colleagues provided that they first agree to be bound by these terms and conditions. If you use this data, please cite the main ShapeNet technical report and the… See the full description on the dataset page: https://huggingface.co/datasets/ShapeNet/ShapeNetSem-archive.

demo-org/diabetes

demo-org

Dataset Card for Auditor_Review This file is a copy, the original version is hosted at data.world

ShapeNet/shapenetcore-glb

ShapeNet

This repository contains ShapeNetCore (v2) in GLB format, a subset of ShapeNet.ShapeNetCore is a densely annotated subset of ShapeNet covering 55 common object categories with ~51,300 unique 3D models. Each model in ShapeNetCore are linked to an appropriate synset in WordNet 3.0. If you use ShapeNet data, you agree to abide by the ShapeNet terms of use. You are only allowed to redistribute the data to your research associates and colleagues provided that they first agree to be bound by… See the full description on the dataset page: https://huggingface.co/datasets/ShapeNet/shapenetcore-glb.

indonesian-nlp/librivox-indonesia

indonesian-nlp

Dataset Card for LibriVox Indonesia 1.0 Dataset Summary The LibriVox Indonesia dataset consists of MP3 audio and a corresponding text file we generated from the public domain audiobooks LibriVox. We collected only languages in Indonesia for this dataset. The original LibriVox audiobooks or sound files' duration varies from a few minutes to a few hours. Each audio file in the speech dataset now lasts from a few seconds to a maximum of 20 seconds. We converted… See the full description on the dataset page: https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia.

bigbio/biosses

bigbio

BIOSSES computes similarity of biomedical sentences by utilizing WordNet as the general domain ontology and UMLS as the biomedical domain specific ontology. The original paper outlines the approaches with respect to using annotator score as golden standard. Source view will return all annotator score individually whereas the Bigbio view will return the mean of the annotator score.

zeroshot/twitter-financial-news-topic

zeroshot

Dataset Description The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their topic. The dataset holds 21,107 documents annotated with 20 labels: topics = { "LABEL_0": "Analyst Update", "LABEL_1": "Fed | Central Banks", "LABEL_2": "Company | Product News", "LABEL_3": "Treasuries | Corporate Debt", "LABEL_4": "Dividend"… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-topic.

jonathanli/law-stack-exchange

jonathanli

Dataset Card for Law Stack Exchange Dataset Dataset Summary Dataset from the Law Stack Exchange, as used in "Parameter-Efficient Legal Domain Adaptation". Citation Information @inproceedings{li-etal-2022-parameter, title = "Parameter-Efficient Legal Domain Adaptation", author = "Li, Jonathan and Bhambhoria, Rohan and Zhu, Xiaodan", booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022", month =… See the full description on the dataset page: https://huggingface.co/datasets/jonathanli/law-stack-exchange.

ai-forever/school_notebooks_RU

ai-forever

School Notebooks Dataset The images of school notebooks with handwritten notes in Russian. The dataset annotation contain end-to-end markup for training detection and OCR models, as well as an end-to-end model for reading text from pages. Annotation format The annotation is in COCO format. The annotation.json should have the following dictionaries: annotation["categories"] - a list of dicts with a categories info (categotiy names and indexes).… See the full description on the dataset page: https://huggingface.co/datasets/ai-forever/school_notebooks_RU.

pysentimiento/spanish-tweets

pysentimiento

spanish-tweets A big corpus of tweets for pretraining embeddings and language models Dataset Summary A big dataset of (mostly) Spanish tweets for pre-training language models (or other representations). Supported Tasks and Leaderboards Language Modeling Languages Mostly Spanish, but some Portuguese, English, and other languages. Dataset Structure Data Fields tweet_id: id of the tweet… See the full description on the dataset page: https://huggingface.co/datasets/pysentimiento/spanish-tweets.

cannlytics/cannabis_results

cannlytics

Cannabis results is a dataset of curated cannabis lab test results. The dataset consists of sub-datasets for each state with any public cannabis lab tests, as well as a sub-dataset that includes all results.

opentargets/clinical_trial_reason_to_stop

opentargets

Dataset Card for Clinical Trials's Reason to Stop Dataset Summary This dataset contains a curated classification of more than 5000 reasons why a clinical trial has suffered an early stop. The text has been extracted from clinicaltrials.gov, the largest resource of clinical trial information. The text has been curated by members of the Open Targets organisation, a project aimed at providing data relevant to drug development. All 17 possible classes have been… See the full description on the dataset page: https://huggingface.co/datasets/opentargets/clinical_trial_reason_to_stop.

dclure/laion-aesthetics-12m-umap

dclure

LAION-Aesthetics :: CLIP → UMAP This dataset is a CLIP (text) → UMAP embedding of the LAION-Aesthetics dataset - specifically the improved_aesthetics_6plus version, which filters the full dataset to images with scores of > 6 under the "aesthetic" filtering model. Thanks LAION for this amazing corpus! The dataset here includes coordinates for 3x separate UMAP fits using different values for the n_neighbors parameter - 10, 30, and 60 - which are broken out as separate columns… See the full description on the dataset page: https://huggingface.co/datasets/dclure/laion-aesthetics-12m-umap.

lambdalabs/pokemon-blip-captions

lambdalabs

Notice of DMCA Takedown Action We have received a DMCA takedown notice from The Pokémon Company International, Inc. In response to this action, we have taken down the dataset. We appreciate your understanding.

Bingsu/openwebtext_20p

Bingsu

openwebtext_20p first 20% of openwebtext