Model Description
bert-base-german-cased_cimt-location is a fine-tuned BERT model that is built to predict location phrases using the B(beginning, LABEL_2)-I(inside, LABEL_1)-O(outside, LABEL_0) label schema.
Specifically, this model is a bert-base-german-cased that was fine-tuned on https://github.com/juliaromberg/cimt-geographic-location-dataset.
Background
This work is based on research in the project CIMT, which investigates the chances and challenges of involving citizens in political decisions in the context of sustainable mobility transitions. (for more information, visit https://www.cimt-hhu.de/en/)
Details & Evaluation Results
Can be found in the corresponding publication https://www.cimt-hhu.de/wp-content/uploads/2023/11/Padjman_Projektarbeitsbericht.pdf.
Usage
from transformers import BertForTokenClassification, BertTokenizer
tokenizer = BertTokenizer.from_pretrained("juliaromberg/bert-base-german-cased_cimt-location")
model = BertForTokenClassification.from_pretrained("juliaromberg/bert-base-german-cased_cimt-location")
Citation
https://www.cimt-hhu.de/wp-content/uploads/2023/11/Padjman_Projektarbeitsbericht.pdf
- Downloads last month
- 8