Luminex NNUE

A tiny neural network for chess position evaluation, trained for the Luminex chess engine.

Model Details

Property Value
Architecture 768 β†’ 32 β†’ 1
Parameters 24,641
File size 48.2 KB (int16 quantized)
Activation Clipped ReLU (hidden), Sigmoid (output)
Input 768 binary features (12 piece types Γ— 64 squares)
Output Win probability [0, 1]

Training

Property Value
Data 1,000,000 real Stockfish-evaluated positions
Source mateuszgrzyb/lichess-stockfish-normalized
Epochs 100
Best val loss 0.034940 (MSE)
Optimizer Adam (lr=0.001, cosine annealing)
Hardware Google Colab free T4 GPU
Training time ~20 minutes

Files

  • luminex-nnue-32.bin β€” Quantized int16 weights for C++ engine inference
  • luminex-nnue-32.pt β€” PyTorch checkpoint for retraining

Binary Format

5 bytes    β€” magic "LNNUE"
int32      β€” version (1)
int32      β€” input size (768)
int32      β€” hidden size (32)
int32      β€” L1_SCALE (255)
int32      β€” OUT_SCALE (64)
int16[32Γ—768] β€” feature transformer weights
int16[32]     β€” feature transformer biases
int16[1Γ—32]   β€” output weights
int16[1]      β€” output bias

Usage

Place luminex-nnue-32.bin next to the Luminex executable. The engine loads it at startup automatically.

License

MIT

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Dataset used to train changcheng967/luminex-nnue