datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
klue-mrc-bm25MRC-psycholinguistic-database
MRC Psycholinguistic Database
This is the complete MRC psycholinguistic database as found on https://websites.psychology.uwa.edu.au/school/mrcdatabase/uwa_mrc.htm.
Usage
This dataset is ideal for training and evaluating machine learning models for English word concreteness.
Acknowledgments
We extend our heartfelt gratitude to all the authors of the original dataset.
License
This dataset is made available under the MIT license.
spotify_datasetstore-sales-time-series-forecasting
taken from this Kaggle competition:
Dataset Description
In this competition, you will predict sales for the thousands of product families sold at Favorita stores located in Ecuador. The training data includes dates, store and product information, whether that item was being promoted, as well as the sales numbers. Additional files include supplementary information that may be useful in building your models.
File Descriptions and Data Field Information… See the full description on the dataset page: https://huggingface.co/datasets/mrcksggcfc/store-sales-time-series-forecasting.VSMRC-mrc-ABCD
VSMRC/mrc (bản tách cột A/B/C/D)
Dataset này là gì
Đây là bản định dạng lại (reformatted / derived) của dataset gốc VSMRC/mrc — phần multiple-choice reading comprehension trong bộ VSMRC (Vietnamese Text Segmentation and Multiple-Choice Reading Comprehension Dataset), do nhóm tác giả tại Đại học
Công nghệ, ĐHQGHN công bố.
Dataset gốc đã có sẵn cột choices (list Python) và correctchoice (số nguyên 0-3) — bản này chỉ map lại thành các cột A, B, C, D, answer cho khớp… See the full description on the dataset page: https://huggingface.co/datasets/p-storm/VSMRC-mrc-ABCD.sentinelng-data-grid
SentinelNG Data Grid Dataset
This repository contains a CSV-based data-grid resource for SentinelNG. The primary artifact is a tabular dataset intended to support grid, location, or structured alert workflows in the SentinelNG ecosystem.
Working with the data
Load the CSV with a tool that preserves column names and types, then inspect missing values, coordinate or identifier semantics, and duplicate rows before use. Do not infer geographic or security meaning from… See the full description on the dataset page: https://huggingface.co/datasets/MR-CODESPIKE/sentinelng-data-grid.ground-truth-ob
Ground Truth OB
This repository contains ground_truth_kb.csv, a tabular ground-truth or knowledge-base resource. The current repository is deliberately small and contains no executable training or evaluation script.
Recommended use
Load the CSV, inspect its column names and encoding, validate identifiers and labels, and record the provenance of every ground-truth field before joining it with model outputs. Keep an immutable copy of the raw file and create derived… See the full description on the dataset page: https://huggingface.co/datasets/MR-CODESPIKE/ground-truth-ob.news-mrc-dataset-200real-yt-omniVN-Database
Visual Novels Dataset
This dataset contains a collection of visual novel scripts sourced from alpindale/visual-novels.
Converted into Hugging Face and, by extension. datasets-compatible format.
idk_mrc_nli_chunkingYou can download this Dataset just like this:
data_files = {"train": "data_nli_train_chunking_df.csv",
"validation": "data_nli_val_chunking_df.csv",
"test": "data_nli_test_chunking_df.csv"}
dataset = load_dataset("muhammadravi251001/idk_mrc_nli_chunking", data_files=data_files)
This is some modification from IDK-MRC dataset to IDK-MRC-NLI dataset. By convert QAS dataset to NLI dataset. You can find the original IDK-MRC in this link:… See the full description on the dataset page: https://huggingface.co/datasets/muhammadravi251001/idk_mrc_nli_chunking.yt-market-signal-7k
This dataset is a synthetic one created using Gemini. It contains 7k+ collection of yt video titles, descriptions and their corresponding labels.
This dataset is created keeping in mind to analyse Why the market cares about the content
idk-mrc-nliYou can download this Dataset just like this (if you only need: premise, hypothesis, and label column):
from datasets import load_dataset, Dataset, DatasetDict
import pandas as pd
data_files = {"train": "data_nli_train_df.csv",
"validation": "data_nli_val_df.csv",
"test": "data_nli_test_df.csv"}
dataset = load_dataset("muhammadravi251001/idk-mrc-nli", data_files=data_files)
selected_columns = ["premise", "hypothesis", "label"]
# selected_columns =… See the full description on the dataset page: https://huggingface.co/datasets/muhammadravi251001/idk-mrc-nli.yt-strategic-intent-9kThis dataset is a synthetic strategic intent corpus generated using Google Gemini, containing approximately 10,000 rows of labeled examples.
It is designed to answer the question “What does the audience want?” with 7 intents:
Build
Awareness
Career
Decide
Evaluate
Inspiration
Learn and
Predict
The dataset provides a structured foundation for training text classification models that uncover audience desires and strategic drivers behind YouTube and business-related content.
idk_mrc_nli_nerYou can download this Dataset just like this:
data_files = {"train": "data_nli_train_ner_df.csv",
"validation": "data_nli_val_ner_df.csv",
"test": "data_nli_test_ner_df.csv"}
dataset = load_dataset("muhammadravi251001/idk_mrc_nli_ner", data_files=data_files)
This is some modification from IDK-MRC dataset to IDK-MRC-NLI dataset. By convert QAS dataset to NLI dataset. You can find the original IDK-MRC in this link:… See the full description on the dataset page: https://huggingface.co/datasets/muhammadravi251001/idk_mrc_nli_ner.yt-tech-comments-datasetThis dataset is a synthetic one generated using Gemini for the task youtube comment sentiment analysis. It contains ~11k rows.
Luminous-OpusConverted from ChaoticNeutrals/Luminous_Opus
MRC