Datasets:
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README.md
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## Dataset Card for m-WildVision
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### Dataset Details
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The m-WildVision dataset is a multilingual multimodal LLM evaluation set. This dataset was created by translating the prompts from the originally English-only [WildVision (vision_bench_0617)](https://arxiv.org/abs/2406.11069) test dataset using Google Translate API v3 to 22 languages.
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This dataset covers 23 languages: Arabic (arb_Arab), Chinese (zho_Hans), Czech (ces_Latn), Dutch (nld_Latn), English (eng_Latn), French (fra_Latn), German (deu_Latn), Greek (ell_Grek), Hebrew (heb_Hebr), Hindi (hin_Deva), Indonesian (ind_Latn), Italian (ita_Latn), Japanese (jpn_Jpan), Korean (kor_Hang), Persian (fas_Arab), Polish (pol_Latn), Portuguese (por_Latn), Romanian (ron_Latn), Russian (rus_Cyrl), Spanish (spa_Latn), Turkish (tur_Latn), Ukrainian (ukr_Cyrl), and Vietnamese (vie_Latn).
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### Load with Datasets
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To load this dataset with Datasets, you'll need to install Datasets as `pip install datasets --upgrade` and then use the following code:
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## Dataset Card for m-WildVision
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<img src="mwildvision2.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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### Dataset Details
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The m-WildVision dataset is a multilingual multimodal LLM evaluation set. This dataset was created by translating the prompts from the originally English-only [WildVision (vision_bench_0617)](https://arxiv.org/abs/2406.11069) test dataset using Google Translate API v3 to 22 languages.
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This dataset covers 23 languages: Arabic (arb_Arab), Chinese (zho_Hans), Czech (ces_Latn), Dutch (nld_Latn), English (eng_Latn), French (fra_Latn), German (deu_Latn), Greek (ell_Grek), Hebrew (heb_Hebr), Hindi (hin_Deva), Indonesian (ind_Latn), Italian (ita_Latn), Japanese (jpn_Jpan), Korean (kor_Hang), Persian (fas_Arab), Polish (pol_Latn), Portuguese (por_Latn), Romanian (ron_Latn), Russian (rus_Cyrl), Spanish (spa_Latn), Turkish (tur_Latn), Ukrainian (ukr_Cyrl), and Vietnamese (vie_Latn).
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### Load with Datasets
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To load this dataset with Datasets, you'll need to install Datasets as `pip install datasets --upgrade` and then use the following code:
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