attention_to_gif VS how-do-vits-work

Compare attention_to_gif vs how-do-vits-work and see what are their differences.

attention_to_gif

Visualize transition of attention weights across layers in a Transformer as a GIF (by valayDave)

how-do-vits-work

(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?" (by xxxnell)
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attention_to_gif how-do-vits-work
1 3
1 784
- -
4.4 0.0
about 3 years ago almost 2 years ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

attention_to_gif

Posts with mentions or reviews of attention_to_gif. We have used some of these posts to build our list of alternatives and similar projects.

how-do-vits-work

Posts with mentions or reviews of how-do-vits-work. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing attention_to_gif and how-do-vits-work you can also consider the following projects:

bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

Parallel-Tacotron2 - PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

awesome-fast-attention - list of efficient attention modules

MPViT - [CVPR 2022] MPViT:Multi-Path Vision Transformer for Dense Prediction

mmdetection - OpenMMLab Detection Toolbox and Benchmark

vit-explain - Explainability for Vision Transformers

query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION