# teknium1/GPTeacher

A collection of modular datasets generated by GPT-4, General-Instruct - Roleplay-Instruct - Code-Instruct - and Toolformer

Repository: https://github.com/teknium1/GPTeacher
Canonical: https://ross.abutalabs.com/products/gpteacher
Language: Python
License: MIT
License Family: permissive
Last push: 2023-09-15T11:30:34+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 89
- inputs: {"age_days": 1249, "days_push": 1083, "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 1667, forks 166 (observed 2026-08-28T04:05:19.652407+00:00)

## What it is
GPTeacher is a collection of modular instruction-tuning datasets generated by GPT-4, including General-Instruct, Roleplay-Instruct, Code-Instruct, and Toolformer subsets in Alpaca-compatible format. It is intended for fine-tuning large language models on instruction-following, roleplay, coding, and tool-use tasks.

## Use cases
- fine-tune an LLM on instruction-following data
- get roleplay training data for a chatbot
- download GPT-4 generated instruction datasets in alpaca format
- train a model to use tools like search and python
- find code instruction datasets for codegen fine-tuning
- build a chatbot with chain-of-thought reasoning examples

## When to choose
- you need ready-made instruction-tuning data in Alpaca format
- you want diverse GPT-4 generated examples including roleplay and tool use
- you are fine-tuning an open LLM and want modular, similarity-cleaned datasets

## When to avoid
- you need a maintained, actively updated dataset
- you require guaranteed data licensing provenance for commercial use
- you want raw generation prompts or the full data pipeline

## Facets
- artifact type: dataset
- maturity: maintenance
- function: data-generation, machine-learning, llm-training
- domain: large-language-models, machine-learning, artificial-intelligence
- platform: python
- tags: instruction-tuning, gpt-4, alpaca-format, fine-tuning, roleplay, toolformer, synthetic-data, natural-language-processing

## Member repositories
- teknium1/GPTeacher (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:19.652407+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 2026-08-30T03:42:53.933010+00:00, confidence not recorded.
  - readme: https://github.com/teknium1/GPTeacher (fetched 2026-08-28T04:05:19.652407+00:00, sha 6578e4cc6b75)
- Data as of 2026-08-30T08:39:29.467469+00:00.