# lmmlzn/Awesome-LLMs-Datasets

Summarize existing representative LLMs text datasets.

Repository: https://github.com/lmmlzn/Awesome-LLMs-Datasets
Canonical: https://ross.abutalabs.com/products/awesome-llms-datasets
License: Apache-2.0
License Family: permissive
Last push: 2026-03-11T03:47:03+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 35, longevity 68
- inputs: {"age_days": 959, "days_push": 175, "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 1480, forks 147 (observed 2026-08-28T04:04:50.830048+00:00)

## What it is
A curated awesome-list summarizing representative text datasets for large language models across pre-training, instruction fine-tuning, preference, evaluation, and traditional NLP dimensions, with newer sections for multimodal and RAG datasets. It accompanies the survey paper 'Datasets for Large Language Models: A Comprehensive Survey' and is regularly updated.

## Use cases
- find pre-training corpora for training an LLM
- discover instruction fine-tuning datasets
- find preference datasets for RLHF
- locate evaluation benchmarks for LLMs
- find RAG training datasets
- survey of LLM datasets for research paper

## When to choose
- you need a comprehensive, categorized index of LLM text datasets
- you want links to papers and dataset details across many languages and domains
- you want a maintained list tied to a peer-reviewed survey

## When to avoid
- you need the datasets themselves rather than references to them
- you need detailed per-dataset metadata, which since 2025 is only summarized with pointers to papers
- you need multimodal dataset coverage beyond the gradually updated sections

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, data-science
- domain: large-language-models, tutorials
- platform: -
- tags: awesome-list, llm-datasets, survey, curated-list, research, natural-language-processing, datasets, web-server

## Member repositories
- lmmlzn/Awesome-LLMs-Datasets (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:50.830048+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 2026-08-30T04:34:15.496450+00:00, confidence not recorded.
  - readme: https://github.com/lmmlzn/Awesome-LLMs-Datasets (fetched 2026-08-28T04:04:50.830048+00:00, sha c9f067a7faeb)
- Data as of 2026-08-30T08:39:29.467469+00:00.