{"data":{"slug":"maxwellrebo-awesome-2vec","name":"awesome-2vec","tagline":"Curated list of 2vec-type embedding models","github_url":"https://github.com/MaxwellRebo/awesome-2vec","owner":"MaxwellRebo","repo":"awesome-2vec","owner_avatar_url":"https://avatars.githubusercontent.com/u/1548819?v=4","primary_language":null,"stars":933,"forks":179,"topics":["awesome","embeddings","list"],"archived":false,"github_pushed_at":"2022-12-08T11:47:32+00:00","maintenance_label":"Dormant","stars_delta_30d":-1,"url":"https://www.graphcanon.com/tools/maxwellrebo-awesome-2vec","markdown_url":"https://www.graphcanon.com/tools/maxwellrebo-awesome-2vec.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/maxwellrebo-awesome-2vec","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=maxwellrebo-awesome-2vec","description":"Curated list of 2vec-type embedding models","homepage_url":null,"license":null,"open_issues":0,"watchers":55,"ai_summary":"MaxwellRebo/awesome-2vec provides a curated collection of 2Vec-type embedding models useful for various AI applications.","readme_excerpt":"# awesome-2vec\nCurated list of 2vec-type embedding models\n\nIf you know of 2vec-style models that are not mentioned here, please do a PR!\n\nFor network/graph-specific embedding models have a look here: https://github.com/chihming/awesome-network-embedding\n\n# The list\n\n**word2vec**\n\nPaper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf\n\nJava: http://deeplearning4j.org/word2vec<br>\n\nC++: https://github.com/jdeng/word2vec\n\nPython: \n- https://radimrehurek.com/gensim/models/word2vec.html\n- https://github.com/danielfrg/word2vec\n\n<hr>\n\n**ASNE**\n\nPaper: https://arxiv.org/abs/2006.04941\n\nPython: https://github.com/jisungyoon/persona2vec\n\n<hr>\n\n**MUSAE**\n\nPaper: https://arxiv.org/abs/1909.13021\n\nPython: https://github.com/benedekrozemberczki/MUSAE\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**SINE**\n\nPaper: https://arxiv.org/abs/1810.06768\n\nPython: https://github.com/benedekrozemberczki/SINE\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**GL2Vec**\n\nPaper: https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**Walklets**\n\nPaper: https://arxiv.org/abs/1605.02115\n\nPython: https://github.com/benedekrozemberczki/walklets\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**Splitter**\n\nPaper: http://epasto.org/papers/www2019splitter.pdf\n\nPython: https://github.com/benedekrozemberczki/Splitter\n\n<hr>\n\n**AttentionWalk**\n\nPaper: http://papers.nips.cc/paper/8131-watch-your-step-learning-node-embeddings-via-graph-attention\n\nPython: https://github.com/benedekrozemberczki/AttentionWalk\n\n<hr>\n\n**role2vec**\n\nPaper: https://arxiv.org/abs/1802.02896\n\nPython: https://github.com/benedekrozemberczki/role2vec\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**ASNE**\n\nPaper: https://arxiv.org/abs/1705.04969\n\nPython: https://github.com/benedekrozemberczki/ASNE\n\n<hr>\n\n**diff2vec**\n\nPaper: https://arxiv.org/abs/2001.07463\n\nPython: https://github.com/benedekrozemberczki/diff2vec\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**GEMSEC**\n\nPaper: https://arxiv.org/abs/1802.03997\n\nPython: https://github.com/benedekrozemberczki/GEMSEC\n\n<hr>\n\n**doc2vec**\n\nPaper: https://cs.stanford.edu/~quocle/paragraph_vector.pdf\n\nPython: https://radimrehurek.com/gensim/models/doc2vec.html\n\n<hr>\n\n**graph2vec**\n\nPaper: https://arxiv.org/abs/1707.05005\n\nPython: https://github.com/benedekrozemberczki/graph2vec\n\nPython: https://github.com/benedekrozemberczki/karateclub\n\n<hr>\n\n**tweet2vec**\n\nPaper: https://arxiv.org/abs/1605.03481\n\nPython: https://github.com/bdhingra/tweet2vec\n\n<hr>\n\n**batter-pitcher-2vec**\n\nPython: https://github.com/airalcorn2/batter-pitcher-2vec\n\n<hr>\n\n**Soccer Team Vectors**\nPaper: https://arxiv.org/abs/1908.00698\n\n<hr>\n\n**illustration-2vec**\n\nPython: https://github.com/rezoo/illustration2vec\n\n<hr>\n\n**lda2vec**\n\nPaper: https://arxiv.org/pdf/1605.02019v1.pdf\n\nSlideshare: http://www.slideshare.net/ChristopherMoody3/word2vec-lda-and-introducing-a-new-hybrid-algorithm-lda2vec-57135994\n\nPython: https://github.com/cemoody/lda2vec\n\n<hr>\n\n**sentence2vec**\n\nPython: https://github.com/klb3713/sentence2vec\n\n<hr>\n\n**wiki2vec**\n\nJava/Scala: https://github.com/idio/wiki2vec\n\n<hr>\n\n**topicvec**\n\nPaper: http://bigml.cs.tsinghua.edu.cn/~jun/topic-embedding.pdf\n\nPython: https://github.com/askerlee/topicvec\n\n<hr>\n\n**entity2vec**\n\nPython: https://github.com/ot/entity2vec\n\nPaper: http://www.di.unipi.it/~ottavian/files/wsdm15_fel.pdf\n\n<hr>\n\n**str2vec**\n\nPython: https://github.com/pengli09/str2vec\n\n<hr>\n\n**node2vec**\n\nPaper: https://arxiv.org/abs/1607.00653\n\nPage: https://snap.stanford.edu/node2vec/\n\nPython: https://github.com/aditya-grover/node2vec\n\n<hr>\n\n**item2vec**\n\nPaper: https://arxiv.org/abs/1603.04259\n\n\n<hr>\n\n**author2vec**\n\nPaper: https://www.microsoft.com/en-us/research/publication/author2vec-learning-author-representations-by-combining-content-and-link","github_created_at":"2016-05-21T04:32:50+00:00","created_at":"2026-07-11T11:31:46.639961+00:00","updated_at":"2026-08-22T18:01:57.673553+00:00","categories":[{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"embeddings","name":"embeddings"},{"slug":"list","name":"list"},{"slug":"model","name":"model"}],"trust":{"provenance":{"is_fork":false,"github_id":59341837,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-22T18:01:56.877Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1353,"last_release_at":null,"stars_delta_30d":-1,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:31:47.967Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-22T18:01:57.335Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need a variety of pre-implemented 2Vec embedding models","Looking to compare different 2Vec implementations quickly"],"when_not_to_use":["Seeking specialized, deep integration with a single embedding model type","Project requires real-time tuning or development of unique 2Vec models"],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:07:40.980Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Curated list of various 2Vec embedding models, essential for specific AI applications needing diverse model approaches."}]}}