routing-transformer VS conformer

Compare routing-transformer vs conformer and see what are their differences.

conformer

Implementation of the convolutional module from the Conformer paper, for use in Transformers (by lucidrains)
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routing-transformer conformer
1 1
288 380
1.4% 3.7%
0.0 3.1
over 3 years ago over 1 year ago
Python Python
MIT License 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.

routing-transformer

Posts with mentions or reviews of routing-transformer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-10.
  • Will Transformers Take over Artificial Intelligence?
    5 projects | news.ycombinator.com | 10 Mar 2022
    I would recommend Routing Transformer https://github.com/lucidrains/routing-transformer but the real truth is nothing beats full attention. Luckily, someone recently figured out how to get past the memory bottleneck. https://github.com/lucidrains/memory-efficient-attention-pyt...

conformer

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

What are some alternatives?

When comparing routing-transformer and conformer you can also consider the following projects:

memory-efficient-attention-pyt

tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch

vit-pytorch - Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Perceiver - Implementation of Perceiver, General Perception with Iterative Attention

Compact-Transformers - Escaping the Big Data Paradigm with Compact Transformers, 2021 (Train your Vision Transformers in 30 mins on CIFAR-10 with a single GPU!)

uformer-pytorch - Implementation of Uformer, Attention-based Unet, in Pytorch

memory-efficient-attention-pytorch - Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"

Nystromformer - An implementation of the Nyströmformer, using Nystrom method to approximate standard self attention

enformer-pytorch - Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

mixture-of-experts - A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models

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Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers
Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
www.nutrient.io
featured

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