verbit
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hebrew_punctuation

Transformers

PyTorch

Hebrew

Inference Endpoints

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verbit-research commited on Sep 19

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 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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-## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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 = ("חברת ורביט פיתחה מערכת לתמלול המבוססת על בינה מלאכותית וגורם אנושי ושוקדת על תמלול עדויות ניצולי שואה את "
+        "התוצאות אפשר לראות כבר ברשת בהן חלקים מעדותו של טוביה ביילסקי שהיה מפקד גדוד הפרטיזנים היהודים "
+        "בביילורוסיה")
+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].