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 weightsconfig.yaml
: Training configuration and metricsversion.json
: Model version and metadataadvanced_magnus_predictor.py
: Model loader and predictor classdemo.py
: Example usage scriptrequirements.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 Gamesself-reported0.067
- Top-3 Accuracy on Magnus Carlsen Professional Gamesself-reported0.116
- Top-5 Accuracy on Magnus Carlsen Professional Gamesself-reported0.142