From 9cf873ebb26ed0f1af16c47ac9e3fc4754a7c543 Mon Sep 17 00:00:00 2001 From: PENG Bo <33809201+BlinkDL@users.noreply.github.com> Date: Sun, 27 Mar 2022 19:13:23 +0800 Subject: [PATCH] Update README.md --- README.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index b3e75e8..e5d0dab 100644 --- a/README.md +++ b/README.md @@ -42,7 +42,9 @@ alt="\begin{align*} +alt="\text{softmax}_t(\text{K}_{u,c}) = \frac{\exp(\text{K}_{u,c})}{\sum_{v \leq t}\exp(\text{K}_{v,c})}"> + +**(UPDATE: We are using the original AFT normalization in v2)** Initialize K and R matrices (and the output projection matrix) to ZERO for fast & stable convergence. @@ -54,6 +56,8 @@ alt="W_{t,u,c}=f_h(t-u)\cdot \alpha_h(u) \cdot \beta_h(t)"> Moreover we multiply the final output of Time-mix layer by γ(t). The reason for the α β γ factors, is because the context size is smaller when t is small, and this can be compensated using the α β γ factors. +**(UPDATE: We remove α β γ factors in v2-RNN and restrict W to be of a simple form and hence able to rewrite it as RNN)** + * The Channel-mix is similar to GeGLU (https://arxiv.org/abs/2002.05202) with an extra R factor. Initialize R and W matrices to ZERO for fast & stable convergence. * Finally, we add extra token-shift (time-shift mixing) as in (https://github.com/BlinkDL/minGPT-tuned).