Spaces:
Sleeping
Sleeping
| title: Persian NER | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 4.44.0 | |
| app_file: app.py | |
| pinned: false | |
| # Persian Named Entity Recognition (NER) | |
| This space performs Named Entity Recognition on Persian (Farsi) text using the ParsBERT model. | |
| ## Features | |
| - Identifies person names, organizations, locations, dates, times, money, and percentages | |
| - Highlights entities with color-coding | |
| - Runs on CPU (no GPU required) | |
| - Provides confidence scores for each detected entity | |
| ## Model | |
| - **Model**: HooshvareLab/bert-base-parsbert-ner-uncased | |
| - **Framework**: Transformers + PyTorch | |
| - **Language**: Persian (Farsi) | |
| ## Usage | |
| Simply enter Persian text in the input box and click "Analyze Text" to see the detected entities highlighted in the text. | |
| ## Entity Types | |
| - **PER** (شخص): Person names | |
| - **ORG** (سازمان): Organizations | |
| - **LOC** (مکان): Locations | |
| - **DAT** (تاریخ): Dates | |
| - **TIM** (زمان): Times | |
| - **MON** (پول): Money amounts | |
| - **PCT** (درصد): Percentages | |
| ## Citation | |
| ```bibtex | |
| @article{ParsBERT, | |
| title={ParsBERT: Transformer-based Model for Persian Language Understanding}, | |
| author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri}, | |
| journal={ArXiv}, | |
| year={2020}, | |
| volume={abs/2005.12515} | |
| } | |
| ``` |