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README.md

@@ -1,3 +1,84 @@
 ---
 license: apache-2.0
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 142178930
+  - name: validation
+    num_examples: 71208
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+task_categories:
+- text-generation
+language:
+- ru
+size_categories:
+- 100M<n<1B
 ---
+
+# Cultura-Ru-Edu
+
+The `Cultura-Ru-Edu` dataset consists of Russian educational web pages filtered from the [`uonlp/CulturaX`](https://huggingface.co/datasets/uonlp/CulturaX) dataset.
+
+The dataset creation was inspired by [`HuggingFaceFW/fineweb-edu`](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu), but with a focus on the Russian language.
+By filtering the dataset based on educational criteria, the `Cultura-Ru-Edu` dataset is both high-quality and large enough to train a Russian-focused language model for tasks requiring knowledge of the world.
+
+## Dataset curation
+
+To create this dataset, we annotated a subset with the `Meta-Llama-3-70B-Instruct` model, trained a classifier on it, and then applied it to the entire dataset, keeping only the high-quality samples.
+
+### Annotation
+
+Follow [`deepvk/cultura_ru_edu_llama3_annotations`](https://huggingface.co/datasets/deepvk/cultura_ru_edu_llama3_annotations) to see details about creating the annotation dataset.
+
+### Training classifier
+
+We trained a classifier based on the [`USER-base`](https://huggingface.co/deepvk/USER-base) model.
+Unlike the original FineWeb-Edu pipeline, we used binary classification, where the positive class includes samples with a score of 3 and higher.
+We found this approach more stable due to the high imbalance in the annotation dataset.
+
+### Dataset scoring
+
+We converted the classifier to ONNX format and applied it to the Russian part of the [`uonlp/CulturaX`](https://huggingface.co/datasets/uonlp/CulturaX) dataset.
+The original dataset contained approximately 800 million documents, and after filtration, only 140 million documents remained (~17.5% of the original dataset).
+
+## Dataset information
+
+Each sample contains only one property — `text`, the original text document.
+
+Some notes:
+- This dataset is a filtered version of the larger, multilingual [`uonlp/CulturaX`](https://huggingface.co/datasets/uonlp/CulturaX) dataset. No other information was added or removed.
+- Since the original dataset consists of parsed web pages, there may still be artifacts in the text header or footer. Future work may include detecting and removing such blocks.
+
+## Usage
+
+To use this dataset, one may simply use the `datasets` API.
+
+```python
+from datasets import load_dataset
+
+cultura_ru_edu = load_dataset("deepvk/cultura_ru_edu", split="train", streaming=True)
+
+```
+
+Note that the dataset size is approximately 500GB, so it is better to use streaming or download it directly via Git LFS.
+
+## Citations
+
+```
+@misc{deepvk2024cultura-ru-edu,
+    title={Cultura-Ru-Edu},
+    author={Spirin, Egor and  Sokolov, Andrey},
+    url={https://huggingface.co/datasets/deepvk/cultura_ru_edu},
+    publisher={Hugging Face}
+    year={2024},
+}
+```

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