IcelandicNER BERT

This model was fine-tuned on the MIM-GOLD-NER dataset for the Icelandic language. The MIM-GOLD-NER corpus was developed at Reykjavik University in 2018–2020 that covered eight types of entities:

• Date
• Location
• Miscellaneous
• Money
• Organization
• Percent
• Person
• Time

Dataset Information

Evaluation

The following tables summarize the scores obtained by model overall and per each class.

How To Use

You use this model with Transformers pipeline for NER.

Installing requirements

pip install transformers

How to predict using pipeline

from transformers import AutoTokenizer
from transformers import AutoModelForTokenClassification  # for pytorch
from transformers import TFAutoModelForTokenClassification  # for tensorflow
from transformers import pipeline


model_name_or_path = "m3hrdadfi/icelandic-ner-bert" 
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
model = AutoModelForTokenClassification.from_pretrained(model_name_or_path)  # Pytorch
# model = TFAutoModelForTokenClassification.from_pretrained(model_name_or_path)  # Tensorflow

nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "Kristin manneskja getur ekki lagt frásagnir af Jesú Kristi á hilluna vegna þess að hún sé búin að lesa þær ."

ner_results = nlp(example)
print(ner_results)

Questions?

Post a Github issue on the IcelandicNER Issues repo.

冰岛语NER BERT

该模型在冰岛语的MIM-GOLD-NER数据集上进行了微调。该 MIM-GOLD-NER 语料库是在 Reykjavik University 于2018-2020年开发的，涵盖了八种实体类型：

• 日期
• 地点
• 杂项
• 货币
• 组织
• 百分比
• 人物
• 时间

数据集信息

评估

以下表格总结了模型整体和每个类别的得分。

如何使用

您可以使用Transformers NER管道来使用此模型。

安装要求

pip install transformers

如何使用管道进行预测

from transformers import AutoTokenizer
from transformers import AutoModelForTokenClassification  # for pytorch
from transformers import TFAutoModelForTokenClassification  # for tensorflow
from transformers import pipeline


model_name_or_path = "m3hrdadfi/icelandic-ner-bert" 
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
model = AutoModelForTokenClassification.from_pretrained(model_name_or_path)  # Pytorch
# model = TFAutoModelForTokenClassification.from_pretrained(model_name_or_path)  # Tensorflow

nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "Kristin manneskja getur ekki lagt frásagnir af Jesú Kristi á hilluna vegna þess að hún sé búin að lesa þær ."

ner_results = nlp(example)
print(ner_results)

有问题吗？

在 IcelandicNER Issues 仓库上发布Github问题。