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nabin2004
/
nebium-large
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Text Generation
PyTorch
English
chess
causal-transformer
rope
swiglu
rmsnorm
License:
mit
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Nebium-Large (762M) โ Autoregressive Chess Transformer
Nebium-Large (762M) โ Autoregressive Chess Transformer
Decoder-only causal transformer trained on competitive Lichess UCI coordinate move sequences.
Parameters:
762 Million ($L=36$, $d_{\text{model}}=1280$, $H=20$)
Architecture:
RoPE positional encoding, SwiGLU non-linearity, Pre-RMSNorm
Vocabulary:
5,000-merge BPE
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Chess transformer
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Updated
9 days ago