AI is happening. The future is updating.gliner_large-v2
GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios. This version has been trained on the **NuNER** dataset (commercially permissive). * Paper: https://arxiv.org/abs/2311.08526 * Repository: https://github.com/urchade/GLiNER
GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios. This version has been trained on the **NuNER** dataset (commercially permissive). * Paper: https://arxiv.org/abs/2311.08526 * Repository: https://github.com/urchade/GLiNER