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Transformer

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**Transformer**

What is Transformer?

A Transformer is a deep learning model that adopts the mechanism of self-attention, differentially weighting the significance of each part of the input data. It is used primarily in the field of natural language processing (NLP) but is increasingly used in computer vision. Transformers are known for their parallelization capabilities and their ability to capture long-range dependencies in data, making them effective for tasks like machine translation, text summarization, and image recognition.

Find 1.4k organizations using Transformer on Sumble →

What other technologies are related to Transformer?

Transformer Competitor Technologies

CNN
CNN
Convolutional Neural Networks (CNNs) are an alternative architecture for sequence processing and other tasks where Transformers are used, although they approach the problem differently.
RNN
RNN
Recurrent Neural Networks (RNNs) are another alternative architecture for sequence processing. Transformers have largely superseded RNNs in many NLP tasks due to their ability to parallelize computations.
LSTM
LSTM
Long Short-Term Memory networks (LSTMs) are a specific type of RNN. Like RNNs, they are an alternative to Transformers for sequence modeling but are often outperformed by Transformers.
GNN
GNN
Graph Neural Networks (GNNs) are used for processing graph-structured data, presenting an alternative approach to problems where Transformers might also be applied, although on different data types.
diffusion model
diffusion model
Diffusion models are another type of generative model, which present an alternative approach to problems where Transformers might also be applied
VAE
VAE
Variational Autoencoders (VAEs) are generative models that provide an alternative approach for tasks like data generation and representation learning, areas where Transformers are also used.
Number of organizations that mention technology
1,414
Transformer
1,627
CNN
1,146
RNN
1,196
LSTM
206
GNN
63
diffusion model
314
VAE
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Transformer Complementary Technologies

distributed training
distributed training
Distributed training is a technique used to train large models like Transformers more efficiently by distributing the workload across multiple machines.
BERT
BERT
BERT is a specific Transformer-based model used for NLP tasks. It's an example of how the Transformer architecture is applied.
PyTorch
PyTorch
PyTorch is a deep learning framework often used to implement and train Transformer models.
Number of organizations that mention technology
1,414
Transformer
59
distributed training
3,157
BERT
29,262
PyTorch
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Which job functions commonly mention Transformer?

Machine Learning
0.6% of all Machine Learning jobs mention Transformer
View 602 jobs on Sumble
AI Engineer
0.4% of all AI Engineer jobs mention Transformer
View 333 jobs on Sumble
Research Scientist
0.2% of all Research Scientist jobs mention Transformer
View 93 jobs on Sumble
Data Scientist
0.2% of all Data Scientist jobs mention Transformer
View 440 jobs on Sumble
Data, Analytics & Machine Learning
0.1% of all Data, Analytics & Machine Learning jobs mention Transformer
View 1.5k jobs on Sumble
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Which organizations are mentioning Transformer?

Transformer
ABB
Utilities 
34 team
mention Transformer
↗
 984 people
use Transformer
↗
Transformer
Qualcomm
Scientific and Technical Services 
20 team
mention Transformer
↗
 16 people
use Transformer
↗
Transformer
Amazon
Retail Trade 
19 team
mention Transformer
↗
 141 people
use Transformer
↗
Transformer
Wärtsilä Corporation
Utilities 
16 team
mention Transformer
↗
 34 people
use Transformer
↗
Transformer
ByteDance
Scientific and Technical Services 
14 team
mention Transformer
↗
 2 people
use Transformer
↗
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