Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
For questions related to the transformer, which is a deep machine learning model introduced in 2017 in the paper "Attention Is All You Need", used primarily in the field of natural language processing (NLP).
32
votes
Accepted
How can Transformers handle arbitrary length input?
Let's say we use a transformer model with 512 limit of sequence length, then we pass a input sequence of 103 tokens. We padded it to 512 tokens. …
1
vote
Accepted
Do transformers have success in other domains different than NLP?
When it talks to other domains such as image or music, using transformer will always face a problem of sequence length limitation. … To the best of my knowledge, the bottleneck of self-attention which uses a $n^2$ matrix quite limits transformer being applied to other domains. …