AI article
Training for quantization: QAT, 1-bit BitNet and 1.58-bit weights
Community description: Quantization-aware training, why BitNet keeps a hidden high-precision weight, and where 1.58 bits comes from.
Dev.to | Oct 17, 2026 | Susheem Koul
Automated excerpt
QAT: you put the quantization of weights inside the training loop. The latent weights are a training-time scaffold. Interactive pages: slope and curvature, latent weights.
Selected automatically from source text; not independently written or fact-checked. Read the original for full context.