NYTK / named-entity-recognition-nerkor-hubert-hungarian

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token-classification

Introduction of named-entity-recognition-nerkor-hubert-hungarian

Model Details of named-entity-recognition-nerkor-hubert-hungarian

Hungarian Named Entity Recognition Model with huBERT

For further models, scripts and details, see our demo site .

  • Pretrained model used: SZTAKI-HLT/hubert-base-cc
  • Finetuned on NYTK-NerKor
  • NE categories are: PER, LOC, MISC, ORG
Limitations
  • max_seq_length = 128
Results

F-score: 90.18%

Usage with pipeline
from transformers import pipeline

ner = pipeline(task="ner", model="NYTK/named-entity-recognition-nerkor-hubert-hungarian")
input_text = "A Kovácsné Nagy Erzsébet nagyon jól érzi magát a Nokiánál, azonban a Németországból érkezett Kovács Péter nehezen boldogul a beilleszkedéssel."

print(ner(input_text, aggregation_strategy="simple"))
Citation

If you use this model, please cite the following paper:

@inproceedings {yang-language-models,
    title = {Training language models with low resources: RoBERTa, BART and ELECTRA experimental models for Hungarian},
    booktitle = {Proceedings of 12th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2021)},
    year = {2021},
    publisher = {IEEE},
    address = {Online},
    author = {Yang, Zijian Győző and Váradi, Tamás},
    pages = {279--285}
}

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named-entity-recognition-nerkor-hubert-hungarian install

named-entity-recognition-nerkor-hubert-hungarian is an open source model from GitHub that offers a free installation service, and any user can find named-entity-recognition-nerkor-hubert-hungarian on GitHub to install. At the same time, huggingface.co provides the effect of named-entity-recognition-nerkor-hubert-hungarian install, users can directly use named-entity-recognition-nerkor-hubert-hungarian installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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