Opir introduces efficient multi-task encoder models trained on a 996-category safety taxonomy that match or exceed larger baselines on most safety benchmarks while using under 100M parameters for edge variants.
GLiNER multi-task: Generalist lightweight model for various information extraction tasks.arXiv preprint arXiv:2406.12925,
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GLiNER-Relex unifies NER and RE in one zero-shot transformer-based model that achieves competitive results on CoNLL04, DocRED, FewRel, and CrossRE.
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Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content
Opir introduces efficient multi-task encoder models trained on a 996-category safety taxonomy that match or exceed larger baselines on most safety benchmarks while using under 100M parameters for edge variants.
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GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction
GLiNER-Relex unifies NER and RE in one zero-shot transformer-based model that achieves competitive results on CoNLL04, DocRED, FewRel, and CrossRE.