Jupyter Notebook · MIT
bentrevett/pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
★ 5.7k
Stars
1.4k forks · 7 open issues
+2.0/wk
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
28.0
Momentum / 100
see the breakdown below
8y ago
Created
last push 2y ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 2.1 | +2.0/wk, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 15.0 | last week ran 2.48× the monthly pace |
| Freshness | 15 | 0.0 | last push 2y ago; decays to zero at 180 days |
| Scale | 15 | 10.9 | 5.7k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 28.0 | sum of the above |
Detail
| Topics | attentioncnn-seq2seqencoder-decoderencoder-decoder-modelgrulstmneural-machine-translationpytorchpytorch-implementationpytorch-implmentionpytorch-nlppytorch-seq2seqpytorch-tutorialpytorch-tutorialsrnnseq2seqsequence-to-sequencetorchtexttransformertutorial |
| Matched on | Learning & Roadmaps (tutorial) |
| Short window | +2 stars over 7 days = 0.3/day |
| Long window | +3 stars over 26 days = 0.1/day |
| Lifetime average | 1.88 stars/day over 3,033 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |