datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
REDDIT_comments
Dataset Card for "REDDIT_comments"
Dataset Summary
Comments of 50 high-quality subreddits, extracted from the REDDIT PushShift data dumps (from 2006 to Jan 2023).
Supported Tasks
These comments can be used for text generation and language modeling, as well as dialogue modeling.
Dataset Structure
Data Splits
Each split corresponds to a specific subreddit in the following list: "tifu", "explainlikeimfive", "WritingPrompts", "changemyview"… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceGECLM/REDDIT_comments.civil_comments
Dataset Card for "civil_comments"
Dataset Summary
The comments in this dataset come from an archive of the Civil Comments
platform, a commenting plugin for independent news sites. These public comments
were created from 2015 - 2017 and appeared on approximately 50 English-language
news sites across the world. When Civil Comments shut down in 2017, they chose
to make the public comments available in a lasting open archive to enable future
research. The original data… See the full description on the dataset page: https://huggingface.co/datasets/google/civil_comments.pushshift-reddit-comments
Dataset Card for "pushshift-reddit"
More Information needed
Algerian-Youtube-Commentsleading-comments
Dataset Card for Dataset Name
Disclaimer: This dataset will be released shortly.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/AISE-TUDelft/leading-comments.mm2_level_comments
Mario Maker 2 level comments
Part of the Mario Maker 2 Dataset Collection
Dataset Description
The Mario Maker 2 level comment dataset consists of 31.9 million level comments from Nintendo's online service totaling around 20GB of data. The dataset was created using the self-hosted Mario Maker 2 api over the course of 1 month in February 2022.
How to use it
The Mario Maker 2 level comment dataset is a very large dataset so for most use cases it is recommended to… See the full description on the dataset page: https://huggingface.co/datasets/TheGreatRambler/mm2_level_comments.danish_political_comments
Dataset Card for DanishPoliticalComments
Dataset Summary
The dataset consists of 9008 sentences that are labeled with fine-grained polarity in the range from -2 to 2 (negative to positive). The quality of the fine-grained is not cross-validated and is therefore subject to uncertainties; however, the simple polarity has been cross-validated and therefore is considered to be more correct.
Supported Tasks and Leaderboards
[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/danish_political_comments.reddit-comments-uwaterloo--- Generated Part of README Below ---
Dataset Overview
The goal is to have an open dataset of r/uwaterloo submissions, leveraging PRAW and the Reddit API to get downloads.
Posts are here
Comments are here
Creation Details
This dataset was created by alvanlii/dataset-creator-reddit-uwaterloo
Update Frequency
The dataset is updated custom with the most recent update being 2024-12-12 23:00:00 UTC+0000 where we added 72 new rows.
Licensing… See the full description on the dataset page: https://huggingface.co/datasets/alvanlii/reddit-comments-uwaterloo.treaty-bodies-general-comments
Treaty Bodies General Comments
A paragraph-level dataset of General Comments and General Recommendations
adopted by the nine UN human-rights Treaty Bodies, with concerned-group
labels and document metadata. Companion to the
UNHRD search interface.
Licence
The curated dataset (paragraph segmentation, label annotation, document
metadata enrichment, footnote and section work) is released under
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International… See the full description on the dataset page: https://huggingface.co/datasets/lszoszk/treaty-bodies-general-comments.swe-bench-commentsIncludes the SWE-bench dataset along with the corresponding comments for each instance_id
smart_contract_code_commentscodebase-content-SWE-bench_Verified-with-comments-and-testsAlgerian-Youtube-Comments
Algerian Youtube Comments
55,365 raw YouTube comments on Algeria-related videos for Darija social-text modeling, from the Algerian NLP Collective. Counted 2026-09-17 via the Hub datasets-server (/info?dataset=algerian-nlp/Algerian-Youtube-Comments: 55,365 train rows) and re-counted row-by-row with datasets streaming (load_dataset("algerian-nlp/Algerian-Youtube-Comments", split="train", streaming=True): 55,365 rows).
The default config answers: how do Algerians actually write in… See the full description on the dataset page: https://huggingface.co/datasets/algerian-nlp/Algerian-Youtube-Comments.task1721_civil_comments_obscenity_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1721_civil_comments_obscenity_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1721_civil_comments_obscenity_classification.task1723_civil_comments_sexuallyexplicit_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1723_civil_comments_sexuallyexplicit_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1723_civil_comments_sexuallyexplicit_classification.codebase-content-SWE-bench_Verified-no-comments-and-file-typestask1720_civil_comments_toxicity_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1720_civil_comments_toxicity_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1720_civil_comments_toxicity_classification.naruto-reddit-commentsThis dataset is extracted from Reddit datasets for research purpose
civil_comments
Dataset Card for "civil_comments"
Dataset Summary
The comments in this dataset come from an archive of the Civil Comments
platform, a commenting plugin for independent news sites. These public comments
were created from 2015 - 2017 and appeared on approximately 50 English-language
news sites across the world. When Civil Comments shut down in 2017, they chose
to make the public comments available in a lasting open archive to enable future
research. The original data… See the full description on the dataset page: https://huggingface.co/datasets/abdulahad-dev/civil_comments.stack-dedup-alt-comments
Dataset Description
This is the Python, Java and JavaScript subsets of The Stack (v1.1) after cleaning* and agressive deduplication from stack-dedup-alt-decontaminate with
filtering on comment to code ratio with minimum of 0.01 and maximum of 0.8.
The additional comments filtering removes 26.5% of the dataset's volume which goes from 215GB of text to 170GB.
(*) cleaning: near deduplication + PII redaction + line length & percentage of alphanumeric characters filtering + data… See the full description on the dataset page: https://huggingface.co/datasets/bigcode/stack-dedup-alt-comments.task1724_civil_comments_insult_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1724_civil_comments_insult_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1724_civil_comments_insult_classification.civil_comments_helmrussian-toxic-comments-multilabel
Russian Toxic Comments Multi-label Dataset
Dataset Description
Этот датасет содержит размеченные комментарии на русском языке для задачи многозадачной (multi-task) и мультилейбл (multi-label) бинарной классификации токсичности.
Цель
Обучение модели для автоматического обнаружения трех типов токсичного контента:
Profanity (ненормативная лексика) — мат, оскорбления, нецензурная брань
Threat (угрозы) — явные или скрытые угрозы в адрес других людей… See the full description on the dataset page: https://huggingface.co/datasets/IvanFed/russian-toxic-comments-multilabel.tiktok-product-video-comments
TikTok Product Video Comments 2026
999,930 TikTok comments and inline replies from 17,730 product videos across 12 shopping categories, collected September 10-13, 2026. This is the corpus behind Crawlora's study 17,774 TikTok 'Where Did You Get That?' Comments: Who Gets an Answer.
Files
File
Rows
Bytes
SHA-256
data/videos.parquet
17,730
4,229,777
5aef621072ada8ff852007e810532c13069b3244ffae6c4fe47ff32549e83020
data/comments.parquet
999,930
81,410,979… See the full description on the dataset page: https://huggingface.co/datasets/crawlora-net/tiktok-product-video-comments.python_comments_free_500000jigsaw-toxic-comments
Dataset Card for Jigsaw Toxic Comments
Dataset
Dataset Description
The Jigsaw Toxic Comments dataset is a benchmark dataset created for the Toxic Comment Classification Challenge on Kaggle. It is designed to help develop machine learning models that can identify and classify toxic online comments across multiple categories of toxicity.
Curated by: Jigsaw (a technology incubator within Alphabet Inc.)
Shared by: Kaggle
Language(s) (NLP): English
License: CC0 1.0… See the full description on the dataset page: https://huggingface.co/datasets/anitamaxvim/jigsaw-toxic-comments.danish_political_commentsedreddit-comments-with-rootpersian-sentiment-comments
Dataset Card for Persian Sentiment Comments
Dataset Description
persian-sentiment-comments is a curated dataset of Persian (Farsi) user comments, each annotated with a sentiment label. The dataset is designed for sentiment analysis tasks and is particularly suitable for training and evaluating machine learning models on Persian text data.
The comments are collected from a variety of sources, including online product reviews and user feedback. Each comment is paired with a… See the full description on the dataset page: https://huggingface.co/datasets/aictsharif/persian-sentiment-comments.task1722_civil_comments_threat_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1722_civil_comments_threat_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1722_civil_comments_threat_classification.