how-do-vits-work VS attention_to_gif

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

how-do-vits-work

(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?" (by xxxnell)

attention_to_gif

Visualize transition of attention weights across layers in a Transformer as a GIF (by valayDave)
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how-do-vits-work attention_to_gif
3 1
784 1
- -
0.0 4.4
almost 2 years ago about 3 years ago
Python Python
Apache License 2.0 MIT License
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.

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.

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.

What are some alternatives?

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

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

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

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