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---
library_name: transformers
license: apache-2.0
language:
- he
base_model:
- onlplab/alephbert-base
---
# Hebrew Punctuation model
## Introduction
This model is a fine-tuned version of AlephBERT, designed to restore punctuation in Hebrew spoken language transcripts. It is specifically trained as a post-processing step for Automatic Speech Recognition (ASR) outputs, where punctuation is often missing in raw transcriptions.
## Usage
For now this is the recommended way to use this model:
```
git lfs install
git clone https://huggingface.co/verbit/hebrew_punctuation
cd hebrew_punctuation
```
Once you are in the folder you could do the following:
```
from transformers import BertTokenizer
from src.models import BertForPunctuation
from src.inference import get_prediction
model = BertForPunctuation.from_pretrained("verbit/hebrew_punctuation")
tokenizer = BertTokenizer.from_pretrained("verbit/hebrew_punctuation")
model.eval()
text = ("讞讘专转 讜专讘讬讟 驻讬转讞讛 诪注专讻转 诇转诪诇讜诇 讛诪讘讜住住转 注诇 讘讬谞讛 诪诇讗讻讜转讬转 讜讙讜专诐 讗谞讜砖讬 讜砖讜拽讚转 注诇 转诪诇讜诇 注讚讜讬讜转 谞讬爪讜诇讬 砖讜讗讛 讗转 "
"讛转讜爪讗讜转 讗驻砖专 诇专讗讜转 讻讘专 讘专砖转 讘讛谉 讞诇拽讬诐 诪注讚讜转讜 砖诇 讟讜讘讬讛 讘讬讬诇住拽讬 砖讛讬讛 诪驻拽讚 讙讚讜讚 讛驻专讟讬讝谞讬诐 讛讬讛讜讚讬诐 "
"讘讘讬讬诇讜专讜住讬讛")
punct_text = get_prediction(
model=model,
text=text,
tokenizer=tokenizer,
backward_context=model.config.backward_context,
forward_context=model.config.forward_context,
return_prob=False
)
print(punct_text)
```
## Contact
For any questions or issues, please contact [email protected]. |