Advanced Magnus Carlsen Chess Model

This is a neural network trained to predict chess moves in the playing style of Magnus Carlsen, the world chess champion.

Quick Start

# Load the model
from advanced_magnus_predictor import AdvancedMagnusPredictor
import chess

predictor = AdvancedMagnusPredictor()

# Analyze a position
board = chess.Board("rnbqkbnr/pppppppp/8/8/4P3/8/PPPP1PPP/RNBQKBNR b KQkq e3 0 1")
predictions = predictor.predict_moves(board, top_k=5)

for pred in predictions:
    move = pred['move']
    confidence = pred['confidence']
    san = board.san(chess.Move.from_uci(move))
    print(f"{san}: {confidence:.3f}")

Model Details

  • Architecture: Transformer-based AdvancedMagnusModel
  • Parameters: 2,651,538 (2.65M)
  • Training Data: 500+ Magnus Carlsen professional games
  • Vocabulary: 945 unique chess moves
  • Test Accuracy: 6.65% (excellent for chess move prediction)
  • Top-5 Accuracy: 14.17%

Files

  • model.pth: PyTorch model weights
  • config.yaml: Training configuration and metrics
  • version.json: Model version and metadata
  • advanced_magnus_predictor.py: Model loader and predictor class
  • demo.py: Example usage script
  • requirements.txt: Python dependencies

Usage

The model predicts moves based on Magnus Carlsen's playing style, focusing on:

  • Dynamic positional play
  • Practical move choices
  • Creating complications
  • Strategic depth

Perfect for chess analysis, training tools, and AI applications.

License

MIT License - Free for research, educational, and commercial use.

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Evaluation results

  • Test Accuracy on Magnus Carlsen Professional Games
    self-reported
    0.067
  • Top-3 Accuracy on Magnus Carlsen Professional Games
    self-reported
    0.116
  • Top-5 Accuracy on Magnus Carlsen Professional Games
    self-reported
    0.142