Update readme

README.md

@@ -18,4 +18,39 @@ widget:
   example_title: "کتاب"
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-# Persian Reverse Dictionary
+# Persian Reverse Dictionary
+![Picture](picture.png)
+
+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](https://www.kaggle.com/malekzadeharman/persian-reverse-dictionary-dataset). 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:
+
+```python
+from my_pipeline import PreTrainedPipeline
+
+pipeline = PreTrainedPipeline("path/to/directory")
+
+result = pipeline("وسیله حمل و نقل پرنده.")
+
+print(result)