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README.md

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----
-dataset_info:
-  features:
-  - name: index
-    dtype: int64
-  - name: input
-    dtype: string
-  - name: output
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 26218781
-    num_examples: 7465
-  download_size: 18798954
-  dataset_size: 26218781
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+    # punctuation_restoration
+
+    ## Dataset Summary
+
+    This dataset is designed for **instruction fine-tuning** of large language models (LLMs), especially for the **Qwen3** family, to perform **punctuation restoration** on Mandarin Chinese text.
+
+    It is derived from the [`AWeirdDev/zh-tw-articles-6k`](https://huggingface.co/datasets/AWeirdDev/zh-tw-articles-6k) dataset. The `context` field is processed to create input-output pairs in the Qwen3-style message format.
+
+    - 🔧 **User message**: A cleaned version of the article with all punctuation removed, spaces added where punctuation was, and an instruction prefix.
+    - ✍️ **Assistant message**: The original article with punctuation.
+    - 🧠 **Use Case**: Fine-tuning Qwen3 or similar chat-style LLMs to restore punctuation from flat text.
+
+    ## Format
+
+    Each sample in the dataset follows this structure:
+
+    ```json
+    {
+      "messages": [
+        {
+          "role": "user",
+          "content": "Your task is to restore the punctuations of this article:\nZhe li shi yi ge mei you biao dian de wen zhang ..."
+        },
+        {
+          "role": "assistant",
+          "content": "這裡是一個沒有標點或者標點不全的文章，請你恢復正確的標點符號。"
+        }
+      ]
+    }