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README.md
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# LaBSE-Malach-Multilabel
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A multilabel text classification model fine-tuned on an English subset (Malach ASR) of the Visual History Archive.
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Input text segments consisted of ~350 words on average.
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Given an input string, the model predicts probablites for 1063 keyword IDs from the VHA ontology, sorted by probability.
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# LaBSE-Malach-Multilabel
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A multilabel text classification model fine-tuned on an English subset (Malach ASR) of the Visual History Archive.
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Based on LaBSE pretrained weights but it uses the general Hugging Face framework, not sentence-transformers.
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Input text segments consisted of ~350 words on average.
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Given an input string, the model predicts probablites for 1063 keyword IDs from the VHA ontology, sorted by probability.
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