bojone/attention
some attention implements observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3161
- days_rel: n/a
- days_push: 2478
- n_releases_24m: 0
Adoption not part of the score
1448 stars · 508 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A small Python library providing implementations of the attention mechanism from 'Attention is All You Need' for TensorFlow/Keras. It is no longer actively updated, with users directed to bert4keras for newer versions.
Use cases
- implement attention mechanism in keras
- understand how transformer attention works
- add attention layer to seq2seq model
- reproduce attention is all you need in tensorflow
When to choose
- you need a minimal, readable attention implementation on old TensorFlow/Keras versions
- you want to study the math behind attention layers
When to avoid
- you use modern TensorFlow 2.x or Keras versions
- you need maintained, production-ready transformer libraries
Facets
library · maturity maintenance
machine-learning deep-learning deep-learning machine-learning python attention-mechanism keras tensorflow transformers natural-language-processing
1 source
- readme: https://github.com/bojone/attention · fetched 2026-08-28 · d0f256c21757
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| bojone/attention | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="bojone/attention")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem