File size: 2,452 Bytes
6dc8c30 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
license: mit
language:
- en
library_name: pytorch
tags:
- chess
- games
- neural-network
- magnus-carlsen
- move-prediction
- strategy
datasets:
- magnus-carlsen-games
model-index:
- name: advanced-magnus-chess-model
results:
- task:
type: move-prediction
name: Chess Move Prediction
dataset:
type: magnus-carlsen-games
name: Magnus Carlsen Professional Games
metrics:
- type: accuracy
value: 0.0665
name: Test Accuracy
- type: top-3-accuracy
value: 0.1158
name: Top-3 Accuracy
- type: top-5-accuracy
value: 0.1417
name: Top-5 Accuracy
---
# 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
```python
# 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.
|