GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer
Paper
•
2311.08526
•
Published
•
13
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 is the OpenVINO's Intermediate Representation version with fp16 compression and without it.
WIP
Do you need to deploy? Please check my github: https://github.com/juampahc/skyresh
I will update the model card asap.
WIP
Base model
urchade/gliner_multi-v2.1