# luban-agi/Awesome-Domain-LLM

收集和梳理垂直领域的开源模型、数据集及评测基准。

Repository: https://github.com/luban-agi/Awesome-Domain-LLM
Canonical: https://ross.abutalabs.com/products/awesome-domain-llm
License: MIT
License Family: permissive
Topics: awesome-list, llm, nlp, dataset, paper-list
Last push: 2023-12-26T12:35:03+00:00

## Health v2 (maintenance only)
Score: 28/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 78
- inputs: {"age_days": 1093, "days_push": 981, "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 2581, forks 200 (observed 2026-08-28T04:07:02.448473+00:00)

## What it is
A curated awesome-list collecting open-source domain-specific large language models, datasets, and evaluation benchmarks across verticals like finance, healthcare, law, and cybersecurity. It is a reference catalog rather than runnable software.

## Use cases
- find open-source LLMs for a specific domain like finance or healthcare
- discover evaluation benchmarks for vertical-domain language models
- research domain-adapted LLMs before fine-tuning my own
- find datasets for training a medical or legal chatbot
- compare domain LLMs like FinGPT, LawGPT, and medical models
- keep up with newly released vertical-domain LLM projects

## When to choose
- you need a survey of open-source domain-specific LLMs, datasets, and benchmarks in one place
- you are researching which vertical-domain model or benchmark to adopt

## When to avoid
- you need runnable software or a model itself rather than a curated list of links
- you need up-to-date coverage, since updates appear to have stopped in late 2023

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, llm-inference, nlp
- domain: large-language-models, awesome-lists, artificial-intelligence
- platform: -
- tags: awesome-list, curated-list, domain-specific-llms, datasets, benchmarks, evaluation, natural-language-processing, web-server

## Member repositories
- luban-agi/Awesome-Domain-LLM (main) score 28

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:02.448473+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 2026-08-30T02:22:37.369884+00:00, confidence not recorded.
  - readme: https://github.com/luban-agi/Awesome-Domain-LLM (fetched 2026-08-28T04:07:02.448473+00:00, sha 9072495514db)
- Data as of 2026-08-30T08:39:29.467469+00:00.