multi
Datasets
All datasets matching “multi”MultiArithmultilingual-speech-commands-15lang
Multilingual Speech Commands Dataset (15 Languages, Augmented)
This dataset contains augmented speech command samples in 15 languages, derived from multiple public datasets. Only commands that overlap with the Google Speech Commands (GSC) vocabulary are included, making the dataset suitable for multilingual keyword spotting tasks aligned with GSC-style classification.
Audio samples have been augmented using standard audio techniques to improve model robustness (e.g., time-shifting… See the full description on the dataset page: https://huggingface.co/datasets/artur-muratov/multilingual-speech-commands-15lang.VDR_MEGA_MultiDomain_DocRetrieval
Visual Document Retrieval Dataset
Overview
This dataset is designed for training visual document retrieval models. It combines multiple datasets from the VDR series, Colpali, and LlamaIndex to create the most comprehensive training resource for visual document retrieval tasks.
Dataset Structure
The dataset contains structured fields including unique identifiers with string lengths ranging from 45 to 50 characters, search query text with variable lengths between… See the full description on the dataset page: https://huggingface.co/datasets/racineai/VDR_MEGA_MultiDomain_DocRetrieval.MultiPL-E
Dataset Card for MultiPL-E
Dataset Summary
MultiPL-E is a dataset for evaluating large language models for code
generation that supports 22 programming languages. It takes the OpenAI
HumanEval and the Mostly Basic Python Programs (MBPP) benchmarks and uses little compilers to
translate them to other languages. It is easy to add support for new languages
and benchmarks.
The dataset is divided into several configurations named SRCDATA-LANG, where
SRCDATA is either… See the full description on the dataset page: https://huggingface.co/datasets/nuprl/MultiPL-E.multispan_quorefMultilingualMultiModalClassification
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.