# Hironsan/awesome-embedding-models

A curated list of awesome embedding models tutorials, projects and communities.

Repository: https://github.com/Hironsan/awesome-embedding-models
Canonical: https://ross.abutalabs.com/products/awesome-embedding-models
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: embeddings, embedding-models, word2vec, machine-learning, natural-language-processing, awesome, papers
Last push: 2019-04-07T22:56:01+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3558, "days_push": 2705, "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 1852, forks 250 (observed 2026-08-28T04:05:44.344088+00:00)

## What it is
A curated awesome-list of embedding model resources including papers, courses, datasets, and implementations covering word2vec, GloVe, FastText, ELMo, and BERT. It serves as a reference index for learning about word and sentence embeddings in NLP.

## Use cases
- find papers on word embeddings like word2vec and GloVe
- learn how BERT and contextual embeddings work
- find tutorials on training embedding models
- locate datasets for embedding model research
- find open-source implementations of embedding algorithms

## When to choose
- you want a curated starting point for learning about embedding models
- you need references to foundational NLP embedding papers
- you are researching word and sentence representation techniques

## When to avoid
- you need a runnable embedding model library rather than a link list
- you need up-to-date coverage of modern embedding models after 2019
- you want production embedding inference tools

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning, documentation
- domain: machine-learning, awesome-lists, tutorials
- platform: python
- tags: awesome-list, embeddings, word2vec, glove, fasttext, bert, curated-list, papers, natural-language-processing

## Member repositories
- Hironsan/awesome-embedding-models (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:44.344088+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 2026-08-30T03:16:51.726194+00:00, confidence not recorded.
  - readme: https://github.com/Hironsan/awesome-embedding-models (fetched 2026-08-28T04:05:44.344088+00:00, sha 12757f2d18b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.