# Mooler0410/LLMsPracticalGuide

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

Repository: https://github.com/Mooler0410/LLMsPracticalGuide
Canonical: https://ross.abutalabs.com/products/llmspracticalguide
Homepage: https://arxiv.org/abs/2304.13712v2
License Family: other
Topics: large-language-models, natural-language-processing, nlp, survey
Last push: 2026-04-08T18:26:44+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 76, release rhythm 35, longevity 87
- inputs: {"age_days": 1228, "days_push": 147, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10200, forks 788 (observed 2026-08-28T04:10:39.857841+00:00)

## What it is
A curated awesome-list of practical guide resources for Large Language Models, based on the survey paper 'Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond'. It includes an evolutionary tree of LLMs, example papers, and model licensing/usage restriction notes.

## Use cases
- find papers and resources about large language models
- understand the evolution of LLMs like GPT and BERT
- learn when to use or avoid LLMs for NLP tasks
- check licensing and usage restrictions of LLMs
- get a practical overview of ChatGPT and similar models
- find guides for building LLM applications in production

## When to choose
- you want a curated, survey-backed reading list on LLMs
- you need a visual map of how language models evolved
- you are a practitioner deciding which LLM fits your NLP task

## When to avoid
- you need runnable code or a software library
- you want up-to-the-minute model releases rather than a curated snapshot
- you need formal documentation rather than links and papers

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: large-language-models, tutorials, artificial-intelligence
- platform: -
- tags: awesome-list, llm-survey, curated-resources, evolutionary-tree, chatgpt, natural-language-processing, web-server

## Member repositories
- Mooler0410/LLMsPracticalGuide (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:39.857841+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 2026-08-29T17:19:37.951841+00:00, confidence not recorded.
  - readme: https://github.com/Mooler0410/LLMsPracticalGuide (fetched 2026-08-28T04:10:39.857841+00:00, sha 58272e3af57b)
  - homepage: https://arxiv.org/abs/2304.13712v2 (fetched 2026-08-29T08:19:37.484467+00:00, sha 2a2774a9b53c)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T08:19:37.488019+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T08:19:37.492017+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T08:19:37.493937+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T08:19:37.490113+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.