Sudoku-RWKV
A RWKV model specifically designed to solve Sudoku puzzles.
Product Details
Sudoku-RWKV is a Sudoku problem-solving tool based on the RWKV model, which uses deep learning technology to solve Sudoku problems. This model has been specially trained to handle a large number of Sudoku samples and has a high problem-solving accuracy. Product background information shows that the model used about 2M Sudoku samples during training, covering about 39.2B tokens, with a parameter size of about 12.7M, a vocabulary of 133, and an 8-layer architecture with 320 dimensions per layer. The main advantages of this model are its high efficiency and accuracy, being able to solve any solvable Sudoku puzzle.
Main Features
How to Use
Target Users
The target audience is Sudoku enthusiasts, artificial intelligence researchers, and developers who need Sudoku problem-solving algorithms. Sudoku enthusiasts can use this tool to quickly solve Sudoku puzzles and enjoy the fun of solving problems; artificial intelligence researchers can study and improve this model and explore the application of deep learning in games and logic problem solving; developers can integrate this model into their applications to provide Sudoku problem-solving functions.
Examples
Sudoku enthusiasts use Sudoku-RWKV to solve difficult Sudoku puzzles online.
Artificial intelligence researchers use the Sudoku-RWKV model to conduct academic research and explore model optimization and improvement.
Mobile app developers integrate Sudoku-RWKV into their Sudoku games to provide automatic puzzle solving.
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