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feat: plasticity training signal integration - bitnet_plasticity_rout…
BitNet-MLX Proprietary Blackbox CI
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docs: BitNet plasticity router using CognitiveBlackBox training signa…
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feat: Add vision feature quantization support for BitNet-native image…
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feat: Full ecosystem sync - LowRankAdapter, physics-informed Manifold…
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feat: Integrate advanced ecosystem capabilities - TopologySurgeon, So…
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feat: Add refined BitNet 1.58 ternary kernels + Metal target + CUDA s…
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Iteration 131: Further refine ManifoldFoldingQuantizer toward pure di…
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Iteration 111: Further simplify ManifoldFoldingQuantizer toward pure …
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Iteration 102: Make efficiencies reusable across ecosystem (export co…
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Iteration 98/100: Expand ManifoldFoldingQuantizer with full operation…
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Iteration 97/100: Manifold Folding Quantization - original methodolog…
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Iteration 95/100: TriStateRouter + full hardware-agnostic routing modes
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Iteration 93/100: AMX optimization + NPU backend scaffolding
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Iteration 92/100: Hardware abstraction layer + future backend support…
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Iteration 91/100: Integrate custom ternary matmul kernel into MLXQuan…
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Iteration 89/100: Concrete MLX Metal kernel for ternary matmul
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Iteration 88/100: MLX-native ternary quantization implementation
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Iteration 72/100: Quantization benchmarks for ModelQuantizer
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Iteration 64/100: Tests for Gemma converter + ModelQuantizer
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docs + fix: Update Gemma converter to use the new robust ModelQuantizer
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Iteration 63/100: Beefed up ModelQuantizer + improved Gemma converter
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Iteration 62/100: Gemma 4B to 1.58-bit ternary converter using BitNet…
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Iteration 49/100: ComputeBackend abstraction + MLX implementation for…
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Iteration 48/100: Hardware abstraction layer for future multi-platfor…
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docs: Further improve BitNet-mlx README with more details and clarity
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