Updated README.md

README.md

@@ -1,3 +1,60 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+language:
+- zh
+pretty_name: PerCN
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-classification
+- multi-label-classification
+tags:
+- mbti
+- personality
+- chinese
+- social-media
+---
+
+# PerCN Dataset
+
+## Overview
+PerCN is a Chinese dataset for MBTI personality type prediction. Each sample contains multiple short posts from the same user, and labels are a 4-d binary vector corresponding to the four MBTI dimensions. The texts include typical Chinese social media expressions, emojis, and colloquial phrasing.
+
+## Data Format
+The dataset is provided in `JSONL` format with three splits: `train.jsonl`, `eval.jsonl`, and `test.jsonl`.
+
+Each line is a JSON object with the following fields:
+- `texts`: `List[str]`, multiple texts from the same user (variable length).
+- `labels`: `List[int]`, a length-4 binary vector (0/1).
+
+Example (truncated):
+```json
+{
+  "texts": ["...", "...", "..."],
+  "labels": [0, 1, 0, 1]
+}
+```
+
+## Usage
+Load from local files with `datasets`:
+```python
+from datasets import load_dataset
+
+# Load from local paths
+dataset = load_dataset(
+    "json",
+    data_files={
+        "train": "train.jsonl",
+        "validation": "eval.jsonl",
+        "test": "test.jsonl",
+    },
+)
+
+print(dataset["train"][0]["texts"][:3])
+print(dataset["train"][0]["labels"])  # 4-d binary vector
+```
+
+## Ethics & Use
+- The data contains user-generated content and may include personal or sensitive information. Do not attempt de-anonymization or re-identification.
+- Recommended for research and educational use only. Comply with applicable laws and platform policies.
+