# codertimo/BERT-pytorch

Google AI 2018 BERT pytorch implementation

Repository: https://github.com/codertimo/BERT-pytorch
Canonical: https://ross.abutalabs.com/products/bert-pytorch
Language: Python
License: Apache-2.0
License Family: permissive
Topics: bert, transformer, pytorch, nlp, language-model
Last push: 2023-09-15T12:57:08+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2879, "days_push": 1083, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6527, forks 1311 (observed 2026-08-28T04:09:44.937771+00:00)

## What it is
A PyTorch implementation of Google AI's 2018 BERT model with simple, readable code. It provides CLI tools for building vocabulary and pre-training BERT with masked language modeling and next sentence prediction on your own corpus.

## Use cases
- pre-train a BERT model on my own corpus
- understand how BERT works by reading a simple implementation
- train a masked language model in pytorch
- implement next sentence prediction training
- build a vocabulary file for BERT training

## When to choose
- you want a minimal, easy-to-read BERT implementation for learning or research
- you need to pre-train BERT from scratch on a custom corpus
- you prefer a lightweight pip-installable package over Hugging Face's larger ecosystem

## When to avoid
- you need production-grade, well-verified transformer models with tokenizers and fine-tuning support
- you want the latest model architectures or active community maintenance
- you need multilingual or optimized inference performance

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, nlp, deep-learning
- domain: machine-learning, deep-learning
- platform: python
- tags: bert, transformer, language-model, pytorch, pretraining, natural-language-processing

## Member repositories
- codertimo/BERT-pytorch (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:44.937771+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 2026-08-29T17:44:09.578347+00:00, confidence not recorded.
  - readme: https://github.com/codertimo/BERT-pytorch (fetched 2026-08-28T04:09:44.937771+00:00, sha 4e18f0413b66)
  - registry_pypi: https://pypi.org/pypi/bert-pytorch/json (fetched 2026-08-29T08:40:35.918956+00:00, sha acda9bb2f3d8)
- Data as of 2026-08-30T08:39:29.467469+00:00.