Update README.md

README.md

@@ -59,4 +59,101 @@ dataset_info:
     num_examples: 6907622
   download_size: 20197306953
   dataset_size: 96105803658
+task_categories:
+- text-generation
+language:
+- ru
+size_categories:
+- 1M<n<10M
 ---
+
+
+# Habr dataset
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Description](#description)
+- [Usage](#usage)
+- [Data Instances](#data-instances)
+- [Source Data](#source-data)
+- [Personal and Sensitive Information](#personal-and-sensitive-information)
+
+## Description
+
+**Summary:** Dataset of posts and comments from [pikabu.ru](https://pikabu.ru/), a website that is Russian Reddit/9gag.
+
+**Script:** [convert_pikabu.py](https://github.com/IlyaGusev/rulm/blob/master/data_processing/convert_pikabu.py)
+
+**Point of Contact:** [Ilya Gusev](ilya.gusev@phystech.edu)
+
+**Languages:** Mostly Russian.
+
+
+## Usage
+
+Prerequisites:
+```bash
+pip install datasets zstandard jsonlines pysimdjson
+```
+
+Dataset iteration:
+```python
+from datasets import load_dataset
+dataset = load_dataset('IlyaGusev/pikabu', split="train", streaming=True)
+for example in dataset:
+    print(example["text_markdown"])
+```
+
+## Data Instances
+
+```
+{
+  "id": 69911642,
+  "title": "Что можно купить в Китае за цену нового iPhone 11 Pro",
+  "text_markdown": "...",
+  "timestamp": 1571221527,
+  "author_id": 2900955,
+  "username": "chinatoday.ru",
+  "rating": -4,
+  "pluses": 9,
+  "minuses": 13,
+  "url": "...",
+  "tags": ["Китай", "AliExpress", "Бизнес"],
+  "blocks": {"data": ["...", "..."], "type": ["text", "text"]},
+  "comments": {
+    "id": [152116588, 152116426],
+    "text_markdown": ["...", "..."],
+    "text_html": ["...", "..."],
+    "images": [[], []],
+    "rating": [2, 0],
+    "pluses": [2, 0],
+    "minuses": [0, 0],
+    "author_id": [2104711, 2900955],
+    "username": ["FlyZombieFly", "chinatoday.ru"]
+  }
+}
+```
+
+You can use this little helper to unflatten sequences:
+
+```python
+def revert_flattening(records):
+    fixed_records = []
+    for key, values in records.items():
+        if not fixed_records:
+            fixed_records = [{} for _ in range(len(values))]
+        for i, value in enumerate(values):
+            fixed_records[i][key] = value
+    return fixed_records
+```
+
+
+## Source Data
+
+* The data source is the [Pikabu](https://pikabu.ru/) website.
+* An original dump can be found here: [pikastat](https://pikastat.d3d.info/)
+* Processing script is [here](https://github.com/IlyaGusev/rulm/blob/master/data_processing/convert_pikabu.py). 
+
+## Personal and Sensitive Information
+
+The dataset is not anonymized, so individuals' names can be found in the dataset. Information about the original authors is included in the dataset where possible.