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README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- tabular-classification
+- reinforcement-learning
+tags:
+- sudoku
+- puzzles
+- logic
+- synthetic
+pretty_name: 500k Sudoku Puzzles (9x9)
+size_categories:
+- 100K<n<1M
+configs:
+- config_name: default
+  data_files:
+  - sudoku_dataset_1m.csv
+---
+
+# 1M Sudoku Puzzles (9x9)
+
+A dataset of 1,000,000 unique 9x9 Sudoku puzzles and their corresponding solutions. Each puzzle has between 40 and 60 blank cells, spanning various difficulty levels.
+
+## Dataset Structure
+
+The dataset is provided in a single CSV file with the following columns:
+
+- `puzzle`: 81-character string representing the initial board (0 = blank).
+- `solution`: 81-character string representing the completed board.
+
+### Example Row
+```csv
+puzzle,solution
+00000001040000000000000000... , 526837941413925768...
+```
+
+## Data Generation
+Puzzles were generated using a custom geometric transformation engine based on a seed board and then blanked out randomly. This method ensures all solutions are valid Sudoku boards.
+
+## Usage
+This dataset is designed for training and benchmarking machine learning models (Transformers, CNNs, GNNs) on Sudoku solving tasks.
+
+### Loading with `datasets` library
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("your_username/your_dataset_name")
+print(dataset["train"][0])
+```
+
+## License
+MIT

sudoku_dataset_1m.csv

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