Model Card for German-Austrian Historical NER
This token-classification model aims to perform Named Entity Recognition on German-Austrian historical documents.
The model has been trained using the tagged entities 10319 samples provided by https://nerdpool-api.acdh-dev.oeaw.ac.at/.
The model has been trained to identify entities from the Minutes of the Austian Council of Ministries.
- Developed by: Dimitra Grigoriou
- Shared by: Dimitra Grigoriou
- Model type: token classification
- Language(s) (NLP): German, Austrian German
- License: CC By-4.0
- Finetuned from model : google-bert-case
Uses
- Named Entity Recignition
Direct Use
from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
model = AutoModelForTokenClassification.from_pretrained("demigrigo/mpr_bert_german_ner")
tokenizer = AutoTokenizer.from_pretrained("demigrigo/mpr_bert_german_ner")
nlp = pipeline("token-classification", model=model, tokenizer=tokenizer, aggregation_strategy="average")
text = "Ernennung FML. Peter Zaninis zum Kriegsminister" ##example sentence
print(nlp(text))
Training Details
Training Data
Training data from: https://nerdpool-api.acdh-dev.oeaw.ac.at/
The data transformed into BIO tagging style required by the original model.
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google-bert/bert-base-cased