# openai/gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

Repository: https://github.com/openai/gpt-2
Canonical: https://ross.abutalabs.com/products/gpt-2
Homepage: https://openai.com/blog/better-language-models/
Language: Python
License: NOASSERTION
License Family: other
Topics: paper
Archived: true
Last push: 2024-08-14T10:50:53+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2760, "days_push": 749, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 25021, forks 5908 (observed 2026-08-28T04:11:37.800011+00:00)

## What it is
Official OpenAI repository containing code and pretrained model weights for GPT-2, from the paper 'Language Models are Unsupervised Multitask Learners'. It is explicitly archived and provided as-is with no further updates expected.

## Use cases
- generate text with GPT-2 models
- download and run pretrained GPT-2 model weights
- experiment with GPT-2 for research
- fine-tune GPT-2 on custom text
- study synthetic text detectability and model biases

## When to choose
- you specifically need the original GPT-2 models or to reproduce the 2019 paper
- you are researching model biases, synthetic text detection, or historical language model behavior
- you want a simple starting point for experimenting with small transformer language models

## When to avoid
- you need a maintained library or up-to-date model support
- you want modern instruction-tuned or larger language models for production use
- you need safety-critical or reliable text generation, since GPT-2 is biased and often inaccurate
- you want active community support or bug fixes

## Facets
- artifact type: library
- maturity: abandoned
- function: llm-inference, machine-learning, deep-learning, llm-training
- domain: large-language-models, deep-learning, artificial-intelligence
- platform: python
- tags: gpt-2, language-models, research-code, text-generation, transformers, openai, archived, natural-language-processing, linux, gpu

## Member repositories
- openai/gpt-2 (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:37.800011+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 2026-08-29T16:56:07.309221+00:00, confidence not recorded.
  - readme: https://github.com/openai/gpt-2 (fetched 2026-08-28T04:11:37.800011+00:00, sha cd6e0dd0636d)
- Data as of 2026-08-30T08:39:29.467469+00:00.