https://arxiv.org/abs/2302.07730 close this message arXiv smileybones icon Global Survey In just 3 minutes help us understand how you see arXiv. TAKE SURVEY Skip to main content Cornell University We gratefully acknowledge support from the Simons Foundation and member institutions. arxiv logo > cs > arXiv:2302.07730 [ ] Help | Advanced Search [All fields ] Search arXiv logo Cornell University Logo [ ] GO quick links * Login * Help Pages * About Computer Science > Computation and Language arXiv:2302.07730 (cs) [Submitted on 12 Feb 2023] Title:Transformer models: an introduction and catalog Authors:Xavier Amatriain Download PDF Abstract: In the past few years we have seen the meteoric appearance of dozens of models of the Transformer family, all of which have funny, but not self-explanatory, names. The goal of this paper is to offer a somewhat comprehensive but simple catalog and classification of the most popular Transformer models. The paper also includes an introduction to the most important aspects and innovation in Transformer models. Subjects: Computation and Language (cs.CL) Cite as: arXiv:2302.07730 [cs.CL] (or arXiv:2302.07730v1 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2302.07730 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Xavier Amatriain [view email] [v1] Sun, 12 Feb 2023 01:26:49 UTC (3,568 KB) Full-text links: Download: * PDF * Other formats [by-4] Current browse context: cs.CL < prev | next > new | recent | 2302 Change to browse by: cs References & Citations * NASA ADS * Google Scholar * Semantic Scholar a export bibtex citation Loading... Bibtex formatted citation x [loading... ] Data provided by: Bookmark BibSonomy logo Mendeley logo Reddit logo ScienceWISE logo (*) Bibliographic Tools Bibliographic and Citation Tools [ ] Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) [ ] Litmaps Toggle Litmaps (What is Litmaps?) [ ] scite.ai Toggle scite Smart Citations (What are Smart Citations?) ( ) Code, Data, Media Code, Data and Media Associated with this Article [ ] Links to Code Toggle Papers with Code (What is Papers with Code?) [ ] ScienceCast Toggle ScienceCast (What is ScienceCast?) ( ) Demos Demos [ ] Replicate Toggle Replicate (What is Replicate?) [ ] Spaces Toggle Hugging Face Spaces (What is Spaces?) ( ) Related Papers Recommenders and Search Tools [ ] Connected Papers Toggle Connected Papers (What is Connected Papers?) [ ] Core recommender toggle CORE Recommender (What is CORE?) ( ) About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?) * About * Help * Click here to contact arXiv Contact * Click here to subscribe Subscribe * Copyright * Privacy Policy * Web Accessibility Assistance * arXiv Operational Status Get status notifications via email or slack