SEACrowd/bloom_vist

BLOOM VIST是一个视觉故事讲述数据集，包含62种东南亚本土语言。该数据集由SIL International开发，并与Bloom Library、应用程序和服务相关联。数据集使用Creative Commons许可证发布，每个故事数据点可能有更详细的许可证（如cc-by, cc-by-nc等）。数据集支持的任务是图像描述（Image Captioning）。

BLOOM VIST is a visual storytelling dataset consisting of 62 languages indigenous to Southeast Asia. The dataset is developed by SIL International and associated with Bloom Library, app, and services. It is released under the Creative Commons license family, with each story datapoint potentially having more detailed licensing (e.g., cc-by, cc-by-nc, etc.). The dataset supports the task of image captioning.

原始信息汇总

Bloom Vist 数据集概述

数据集简介

• 名称: Bloom Vist
• 描述: 一个包含62种东南亚本土语言的视觉叙事数据集。
• 所有者: Bloom，由SIL International开发的开源软件，与Bloom Library、app和服务相关联。
• 许可证: Creative Commons 许可证家族（cc），每个故事数据点有更详细的许可信息，如cc-by, cc-by-nc, cc-by-nd, cc-by-sa, cc-by-nc-nd, cc-by-nc-sa。

语言

• 包含62种语言，包括：
  • abc, ahk, bfn, bjn, bkx, brb, brv, bya, bzi, ceb, cgc, cmo, ddg, dmg, dnw, dtp, enc, fil, hil, hro, idt, ilo, ind, jra, kak, khb, khm, kqr, krr, ksw, lhu, lsi, lwl, mdr, mgm, mhx, mkz, mry, msb, mya, nod, nxa, nxl, pag, pce, pea, pmf, psp, sea, sgd, sml, snl, tdt, tet, tha, tkd, tpu, war, wms, yet, yin, zlm

支持的任务

• 任务类别: 图像描述（Image Captioning）

数据集版本

• 源版本: 0.1.0
• SEACrowd版本: 2024.06.20

数据集使用

使用 datasets 库

python from datasets import load_dataset dset = datasets.load_dataset("SEACrowd/bloom_vist", trust_remote_code=True)

使用 seacrowd 库

python import seacrowd as sc

加载数据集使用默认配置

dset = sc.load_dataset("bloom_vist", schema="seacrowd")

检查数据集的所有可用子集（配置名称）

print(sc.available_config_names("bloom_vist"))

使用特定配置加载数据集

dset = sc.load_dataset_by_config_name(config_name="<config_name>")

数据集主页

• Bloom Vist 数据集主页

引用

• 在使用 Bloom Vist 数据集时，请引用以下内容：

@inproceedings{leong-etal-2022-bloom, title = "Bloom Library: Multimodal Datasets in 300+ Languages for a Variety of Downstream Tasks", author = "Leong, Colin and Nemecek, Joshua and Mansdorfer, Jacob and Filighera, Anna and Owodunni, Abraham and Whitenack, Daniel", editor = "Goldberg, Yoav and Kozareva, Zornitsa and Zhang, Yue", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.emnlp-main.590", doi = "10.18653/v1/2022.emnlp-main.590", pages = "8608--8621", }

@article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }