multilingual
MultilingualMultiModalClassification
Additional Information
To load the dataset,
import datasets
ds = datasets.load_dataset("AmazonScience/MultilingualMultiModalClassification", data_dir="wiki-doc-ar-merged")
print(ds)
DatasetDict({
train: Dataset({
features: ['image', 'filename', 'words', 'ocr_bboxes', 'label'],
num_rows: 8129
})
validation: Dataset({
features: ['image', 'filename', 'words', 'ocr_bboxes', 'label'],
num_rows: 1742
})
test: Dataset({
features:… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/MultilingualMultiModalClassification.SWE-bench_Multilingual
SWE-bench Multilingual
Dataset Summary
SWE-bench Multilingual is a dataset that tests systems' ability to resolve real-world GitHub issues across a broad range of programming languages. The original SWE-bench is Python-only; this dataset extends the same task format to 9 languages drawn from 41 popular repositories.
The dataset collects 300 test Issue-Pull Request pairs. Evaluation is performed by unit test verification, using post-PR behavior as the reference solution.
The… See the full description on the dataset page: https://huggingface.co/datasets/SWE-bench/SWE-bench_Multilingual.multilingual_librispeech
Dataset Card for MultiLingual LibriSpeech
Dataset Summary
This is a streamable version of the Multilingual LibriSpeech (MLS) dataset.
The data archives were restructured from the original ones from OpenSLR to make it easier to stream.
MLS dataset is a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of
8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish.… See the full description on the dataset page: https://huggingface.co/datasets/facebook/multilingual_librispeech.M-ABSA
M-ABSA
This repo contains the data for our paper M-ABSA: A Multilingual Dataset for Aspect-Based Sentiment Analysis.
Data Description:
This is a dataset suitable for the multilingual ABSA task with triplet extraction.
All datasets are stored in the data/ folder:
All dataset contains 7 domains.
domains = ["coursera", "hotel", "laptop", "restaurant", "phone", "sight", "food"]
Each dataset contains 21 languages.
langs = ["ar", "da", "de", "en", "es", "fr", "hi"… See the full description on the dataset page: https://huggingface.co/datasets/Multilingual-NLP/M-ABSA.unwebtv-multilingual-audio-archive
UN WebTV Multilingual Audio Archive
This public dataset is a reproducibility-oriented archive of multilingual audio tracks collected from publicly accessible institutional media pages.
Files are grouped by source and published as source-level archives. The accompanying manifests preserve source URLs, language labels, extraction status, and verification metadata. The archive is intended for research and engineering evaluation; downstream users must respect the terms, licenses… See the full description on the dataset page: https://huggingface.co/datasets/hysi-lab/unwebtv-multilingual-audio-archive.OCR-Synthetic-Multilingual-v1
OCR-Synthetic-Multilingual-v1
Dataset Description
Large-scale synthetically generated OCR training dataset for multilingual text detection and recognition. The data was produced using a heavily modified and extended version of SynthDoG (Synthetic Document Generator), originally introduced in the Donut project by Kim et al.
This dataset was used to train Nemotron OCR v2, a state-of-the-art multilingual OCR model that is part of the NVIDIA NeMo Retriever collection.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OCR-Synthetic-Multilingual-v1.