--- license: mit datasets: - kargaranamir/HengamCorpus tags: - span-marker - token-classification - ner - named-entity-recognition pipeline_tag: token-classification inference: false language: - fa --- # Hengam: An Adversarially Trained Transformer for Persian Temporal Tagging # Usage You can use this model directly downloading the utils and requirements files and installing requirements: ```python >>> ! wget https://huggingface.co/kargaranamir/Hengam/raw/main/utils.py >>> ! wget https://huggingface.co/kargaranamir/Hengam/raw/main/requirements.txt >>> ! pip install -r requirements.txt ``` and downloading the models HengamTransA.pth or HengamTransW.pth and building ner pipline: ```python >>> import torch >>> from huggingface_hub import hf_hub_download >>> from utils import * >>> # HengamTransW = hf_hub_download(repo_id="kargaranamir/Hengam", filename="HengamTransW.pth") >>> HengamTransA = hf_hub_download(repo_id="kargaranamir/Hengam", filename="HengamTransA.pth") ``` ```python >>> # ner = NER(model_path=HengamTransW, tags=['B-TIM', 'I-TIM', 'B-DAT', 'I-DAT', 'O']) >>> ner = NER(model_path=HengamTransA, tags=['B-TIM', 'I-TIM', 'B-DAT', 'I-DAT', 'O']) >>> ner('.سلام من و دوستم ساعت ۸ صبح روز سه شنبه رفتیم دوشنبه بازار ') [{'Text': 'ساعت', 'Tag': 'B-TIM', 'Start': 17, 'End': 21}, {'Text': '۸', 'Tag': 'I-TIM', 'Start': 22, 'End': 23}, {'Text': 'صبح', 'Tag': 'I-TIM', 'Start': 24, 'End': 27}, {'Text': 'روز', 'Tag': 'I-TIM', 'Start': 28, 'End': 31}, {'Text': 'سه', 'Tag': 'B-DAT', 'Start': 32, 'End': 34}, {'Text': 'شنبه', 'Tag': 'I-DAT', 'Start': 35, 'End': 39}] ``` ## Citation If you use any part of this repository in your research, please cite it using the following BibTex entry. ```python @inproceedings{mirzababaei-etal-2022-hengam, title = {Hengam: An Adversarially Trained Transformer for {P}ersian Temporal Tagging}, author = {Mirzababaei, Sajad and Kargaran, Amir Hossein and Sch{\"u}tze, Hinrich and Asgari, Ehsaneddin}, year = 2022, booktitle = {Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing}, publisher = {Association for Computational Linguistics}, address = {Online only}, pages = {1013--1024}, url = {https://aclanthology.org/2022.aacl-main.74} } ```