GLiNER-medium-v2.1 is a Hugging Face Space demonstrating a zero-shot named entity recognition model. Users input text and a comma-separated list of desired entity types. The model identifies matching spans with confidence scores and supports options for nested entities. It provides an interactive way to test the GLiNER model's capabilities for flexible information extraction without task-specific fine-tuning.
GLiNER-medium-v2.1, zero-shot NER sits in PulseGate's AI & ML category. It focuses on extracting arbitrary named entities from text without training a specific model for each entity type. It is built as an open-source project for NLP developers and researchers. GLiNER-medium-v2.1, zero-shot NER is free to use. GLiNER-medium-v2.1, zero-shot NER is available on the web, and it can be self-hosted.
It is developed by tomaarsen, and the product first shipped in 2024. Key capabilities include Zero-shot NER, Custom Entity Types, and Confidence Threshold.
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tomaarsen/gliner_medium-v2.1 verified by the PulseGate indexer
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