# SamLynnEvans/Transformer

Transformer seq2seq model, program that can build a language translator from parallel corpus

Repository: https://github.com/SamLynnEvans/Transformer
Canonical: https://ross.abutalabs.com/products/samlynnevans-transformer
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2023-05-19T10:22:41+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2906, "days_push": 1202, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1430, forks 346 (observed 2026-08-28T04:04:42.316441+00:00)

## What it is
A PyTorch implementation of the Transformer seq2seq model designed to build language translators from parallel corpora. It accompanies a tutorial explaining how to code the Transformer architecture from scratch.

## Use cases
- train a language translator from parallel text files
- learn how the transformer model is implemented in pytorch
- build a machine translation model for supported spacy languages
- experiment with transformer hyperparameters like layers and attention heads
- reproduce a seq2seq translation model on a single gpu

## When to choose
- you want a readable, educational transformer implementation for translation
- you have parallel sentence pairs in languages supported by spacy
- you want to train a small seq2seq model on a single consumer gpu

## When to avoid
- you need production-grade translation with subword tokenization and many languages
- you want a maintained library with active development and broad model support
- you need pretrained multilingual models rather than training from scratch

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, nlp, llm-training
- domain: machine-learning, deep-learning
- platform: python, cross-platform
- tags: transformer, seq2seq, pytorch, machine-translation, educational, natural-language-processing, gpu

## Member repositories
- SamLynnEvans/Transformer (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:42.316441+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:37:10.510032+00:00, confidence not recorded.
  - readme: https://github.com/SamLynnEvans/Transformer (fetched 2026-08-28T04:04:42.316441+00:00, sha b7e2277324ae)
- Data as of 2026-08-30T08:39:29.467469+00:00.