vision_transformers_explained

This folder of code contains code and notebooks to supplement the "Vision Transformers Explained" series published on Towards Data Science written by Skylar Callis.

https://github.com/lanl/vision_transformers_explained

Science Score: 62.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • Institutional organization owner
    Organization lanl has institutional domain (www.lanl.gov)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (6.3%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

This folder of code contains code and notebooks to supplement the "Vision Transformers Explained" series published on Towards Data Science written by Skylar Callis.

Basic Info
  • Host: GitHub
  • Owner: lanl
  • License: other
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 46.9 MB
Statistics
  • Stars: 83
  • Watchers: 6
  • Forks: 20
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Citation

README.md

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Vision Transformers Explained

This folder of code contains code and notebooks to supplement the Vision Transformers Explained series written by Skylar Callis for Towards Data Science. These articles can be read on Medium or in their equivalent Jupyter Notebook:

This project were developed by Skylar Callis while working as a post-bachelors student at Los Alamos National Laboratory (LANL) from 2022 - 2024. To see what they are up to these days, visit Skylar's Website .

The Vision Transformers Explained code has been approved by LANL for a BSD-3 open source license under O#4693. The written components have been approved for release as LA-UR-23–33876.

The GitHub page for this code can be found here.

Owner

  • Name: Los Alamos National Laboratory
  • Login: lanl
  • Kind: organization
  • Email: github-register@lanl.gov
  • Location: Los Alamos, New Mexico, USA

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Vision Transformers Explained
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Skylar
    family-names: Callis
    email: sjcallis@lanl.gov
    affiliation: Los Alamos National Laboratory
    orcid: 'https://orcid.org/0009-0009-4133-377X'
repository-code: 'https://github.com/lanl/vision_transformers_explained'
url: >-
  https://towardsdatascience.com/vision-transformers-explained-a9d07147e4c8
abstract: >-
  This folder of code contains code and notebooks to
  supplement the "Vision Transformers Explained" series
  published on Towards Data Science written by Skylar
  Callis.
keywords:
  - machine learning
  - pytorch
  - vision transformers
  - transformers
  - attention
license: BSD-3-Clause

GitHub Events

Total
  • Watch event: 28
  • Fork event: 5
Last Year
  • Watch event: 28
  • Fork event: 5

Committers

Last synced: 11 months ago

All Time
  • Total Commits: 29
  • Total Committers: 1
  • Avg Commits per committer: 29.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 2
  • Committers: 1
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Skylar Callis s****s@l****v 29
Committer Domains (Top 20 + Academic)

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Last synced: 11 months ago

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  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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