Persian Reverse Dictionary

Picture

This project aims to create a Persian reverse dictionary model that suggests a word based on our input explanations. This model is based on Transformer encoders and uses fast text embedding.

Dataset

The dataset used in this work is from this link. This dataset contains 855,217 data from Amid, Moein, and Dehkhoda dictionaries plus Farsnet and Persian Wikipedia.

Overall

Metric Value
Top-10 accuracy 16.72%
Top-100 accuracy 33.89%
Top-10 Synonyms accuracy 42.19%
Top-100 Synonyms accuracy 62.72%

How to use

  1. Clone the repository.
  2. Install the required libraries.
  3. Import the PreTrainedPipeline class from the script.
  4. Instantiate the pipeline object with the path to the directory where the saved model and other required files are located.
  5. Call the pipeline object on an input sentence.

Here's an example usage:

from pipeline import PreTrainedPipeline

pipeline = PreTrainedPipeline("path/to/directory")

result = pipeline("وسیله حمل و نقل پرنده.")

print(result)
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