NoeFlandre/benchmark-llms-landuse-relevance

Land-use relevance benchmark v3-multilingual contains 25,500 sentences in 85 languages, with 300 labeled sentences per language. Each label is yes or no for whether the sentence describes land use, land cover, or geographic environment that could be observed through remote sensing. Evaluation code · Full prompt, methods, pins, and runtime notes Results knowledgator/gliclass-multilang-ultra covers all 85 benchmark languages; its model card lists 20 native training… See the full description on the dataset page: https://huggingface.co/datasets/NoeFlandre/benchmark-llms-landuse-relevance.

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