Training models with ternary quantized weights using PyTorch
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Updated
Jun 12, 2019 - Python
Training models with ternary quantized weights using PyTorch
Colab-friendly BitNet distillation engine: collect KD traces from a teacher, train a ternary Mini-BitNet, and dry-run 7B memory. Multi-provider + Drive/S3
PILON (Primitive-Induced Linear Operator Network) explores a compositional weight parameterization for transformer FFN layers. The goal is to replace dense FFN matrices with shared low-rank primitives plus learned composition weights.
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