# Hannibal046/Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

Repository: https://github.com/Hannibal046/Awesome-LLM
Canonical: https://ross.abutalabs.com/products/awesome-llm
License: CC0-1.0
License Family: permissive
Last push: 2025-07-31T02:38:24+00:00

## Health v2 (maintenance only)
Score: 46/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 34, release rhythm 35, longevity 92
- inputs: {"age_days": 1293, "days_push": 399, "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 27287, forks 2686 (observed 2026-08-28T04:11:47.643588+00:00)

## What it is
A curated awesome-list of resources on Large Language Models, including milestone papers, open LLM checkpoints, training and inference frameworks, evaluation tools, courses, and books. It serves as a reference index rather than executable software.

## Use cases
- find papers about large language models
- discover open-source LLM checkpoints and APIs
- learn about LLM training frameworks
- find courses and tutorials on LLMs
- keep up with trending LLM projects
- compare LLM evaluation tools and leaderboards

## When to choose
- you want a broad, curated starting point for LLM research and tooling
- you need links to milestone LLM papers and open models
- you are exploring the LLM ecosystem before picking specific tools

## When to avoid
- you need runnable software rather than a link collection
- you need exhaustive, up-to-the-minute coverage of every new model
- you need in-depth tutorials rather than an index of resources

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: large-language-models, artificial-intelligence, machine-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, curated-resources, llm, papers, chatgpt

## Member repositories
- Hannibal046/Awesome-LLM (main) score 46

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:47.643588+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 2026-08-29T16:54:33.450567+00:00, confidence not recorded.
  - readme: https://github.com/Hannibal046/Awesome-LLM (fetched 2026-08-28T04:11:47.643588+00:00, sha 8dd45443ca64)
- Data as of 2026-08-30T08:39:29.467469+00:00.