MohammadJRanjbar/persian-sentence-completion

Persian Sentence Completion Classifier

A BERT-based classifier that determines whether a Persian sentence is Complete or Incomplete.
Designed for use in ASR post-processing pipelines (e.g. after speech-to-text).

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

MODEL_ID = "MohammadJRanjbar/persian-sentence-completion"

tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID)
model.eval()

label_map = {0: "Incomplete", 1: "Complete"}

def classify_sentences(sentences, batch_size=16):
    results = []
    for i in range(0, len(sentences), batch_size):
        batch = sentences[i:i+batch_size]
        inputs = tokenizer(batch, return_tensors="pt", padding=True,
                           truncation=True, max_length=128)
        with torch.no_grad():
            outputs = model(**inputs)
            preds = torch.argmax(outputs.logits, dim=-1)
            results.extend([label_map[p.item()] for p in preds])
    return results

# Example
texts = ["امروز هوا خیلی عالی", "امروز هوا خیلی عالی است."]
print(classify_sentences(texts))
# → ['Incomplete', 'Complete']

Citation

If you use this model, please cite the following works:

@misc{kalahroodi2026persianpunclargescaledatasetbertbased,
      title={PersianPunc: A Large-Scale Dataset and BERT-Based Approach for Persian Punctuation Restoration}, 
      author={Mohammad Javad Ranjbar Kalahroodi and Heshaam Faili and Azadeh Shakery},
      year={2026},
      eprint={2603.05314},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2603.05314}, 
}

@misc{kalahroodi2025parsvoicelargescalemultispeakerpersian,
    title = {ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus for Text-to-Speech Synthesis},
    author = {Mohammad Javad Ranjbar Kalahroodi and Heshaam Faili and Azadeh Shakery},
    year = {2025},
    eprint = {2510.10774},
    archivePrefix = {arXiv},
    primaryClass = {cs.SD},
    url = {https://arxiv.org/abs/2510.10774},
}