Runpod ar selfgen nextsteps#1419
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Adds Full Attention Residuals (AttnRes) from Kimi Team paper to the LeakyReLU² + Legal TTT + Parallel Muon stack. Zero-initialized learned softmax depth-attention over all preceding layer outputs replaces fixed x0 global residual. Also updates train_gpt_mlx.py with the same changes for local Apple Silicon testing. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
… lzma-9 Builds on 2026-03-24 AttnRes stack. Five improvements: - MTP_NUM_HEADS=1: free training signal, stripped at export (0 artifact bytes) - GATED_ATTENTION=1: per-head sigmoid gate, ~24KB cost - VALUE_RESIDUAL=1: value-stream skip connection, ~0 bytes - TTT Adam optimizer: replaces SGD for better per-chunk adaptation (lr=2e-4) - lzma preset=9: improved artifact compression, no eval time cost Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Base: LeakyReLU² + Legal TTT + Parallel Muon (1.1194) - MTP_NUM_HEADS=1: free training signal, stripped at export - GATED_ATTENTION=1: per-head sigmoid gate, ~24KB artifact cost - VALUE_RESIDUAL=1: value-stream skip, vr_lambda init [0.0, 1.0] - lzma preset=9: better compression, no eval cost - TTT_USE_ADAM added but off by default (SGD preserved from SOTA) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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