Logo
Explore City Headlines Help
Register Sign In
wehub/labmlai--annotated_deep_learning_paper_implementations
1
0
Fork 0
You've already forked labmlai--annotated_deep_learning_paper_implementations
Code Issues Pull Requests Actions Deployments Models Agent Notes Packages Projects Releases Wiki Activity
Files
main
labmlai--annotated_deep_lea…/labml_nn/transformers/fnet
T
History
wehub-resource-sync 3b90d1192f chore: import upstream snapshot with attribution
2026-07-13 12:19:01 +08:00
..
__init__.py
chore: import upstream snapshot with attribution
2026-07-13 12:19:01 +08:00
experiment.py
chore: import upstream snapshot with attribution
2026-07-13 12:19:01 +08:00
readme.md
chore: import upstream snapshot with attribution
2026-07-13 12:19:01 +08:00

readme.md

FNet: Mixing Tokens with Fourier Transforms

This is a PyTorch implementation of the paper FNet: Mixing Tokens with Fourier Transforms.

This paper replaces the self-attention layer with two Fourier transforms to mix tokens. This is a 7X more efficient than self-attention. The accuracy loss of using this over self-attention is about 92% for BERT on GLUE benchmark.

Reference in New Issue View Git Blame Copy Permalink
Powered by wehub Version: c43b1e3 Page: 65ms Template repo/view: 1ms
Auto
English
Bahasa Indonesia Deutsch English Español Français Gaeilge Italiano Latviešu Magyar nyelv Nederlands Polski Português de Portugal Português do Brasil Suomi Svenska Türkçe Čeština Ελληνικά Български Русский Українська فارسی മലയാളം 日本語 简体中文 繁體中文(台灣) 繁體中文(香港) 한국어
Licenses API