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README.md

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+# Persian NLG
+
+## Dataset Summary
+
+The **Persian NLG Benchmark** is a curated collection of Persian datasets designed to evaluate natural language generation (NLG) capabilities in a variety of tasks, including:
+
+- **Summarization**: Using datasets like **SamSUM-fa** and **PnSummary**  
+- **Machine Translation**: With parallel corpora such as **TEP**, **MIZAN**, and **EPOQUE**  
+- **Question Generation**: Using the **PersianQA** dataset
+
+This benchmark provides a comprehensive view of how Persian-capable models perform on generative tasks that are linguistically and semantically complex.
+
+---
+
+## Supported Tasks and Leaderboards
+
+### Summarization
+The summarization track tests how well models can generate concise and accurate summaries from Persian conversational or formal texts. Relevant columns include input text and human-written summaries.
+
+### Machine Translation
+The translation task evaluates models' performance in translating between Persian, English, and Arabic. The datasets cover multiple domains and include source-target sentence pairs. Evaluation can be done in both directions (e.g., fa→en, en→fa).
+
+### Question Generation
+The question generation task assesses the ability of models to generate meaningful questions based on a given passage and answer. This tests the contextual and semantic understanding of the models in Persian.
+
+---
+
+## Languages
+
+The primary language is **Persian (fa)**, but the machine translation section includes **English (en)** and **Arabic (ar)** as well.
+
+---
+
+## License
+
+This dataset is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
+
+You must give appropriate credit, may not use it for commercial purposes, and may not distribute modified versions of the dataset.
+
+For details, see the [license](LICENSE) file or https://creativecommons.org/licenses/by-nc-nd/4.0/