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What is an encoder decoder model?
In this post, we introduce the encoder decoder structure in some cases known as Sequence to Sequence (Seq2Seq) model. For a better understanding of the structure of this model, previous knowledge on…
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Introduction to Encoder-Decoder Models — ELI5 Way
Discuss the basic concepts of Encoder-Decoder models and it's applications such as language modeling, image captioning, Machine Transliteration RNN and LSTM
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TransformerDecoderLayer
TransformerDecoderLayer is made up of self-attn, multi-head-attn and feedforward network. This standard decoder layer is based on the paper “Attention Is All You Need”. Ashish Vaswani, Noam Shazeer, N...
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TransformerDecoder
TransformerDecoder is a stack of N decoder layers decoder_layer – an instance of the TransformerDecoderLayer() class (required). num_layers – the number of sub-decoder-layers in the decoder (required)...
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Machine Translation(Encoder-Decoder Model) !!
English to Hindi translation using Deep Learning
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— JSON encoder and decoder
json — JSON encoder and decoder Source code: Lib/json/__init__.py JSON (JavaScript Object Notation) , specified by RFC 7159 (which obsoletes RFC 4627 ) and by ECMA-404 , is a lightweight data interch...
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Detangling Decoding
If you held a vinyl record up to your ear, you wouldn’t expect to hear music — no matter how much dust you blew off it. The information that the record contains is encoded in a machine-readable…
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Baby steps in Neural Machine Translation Part 2(Decoder) — Human is solving the challenge given by…
This is the follow-up from part 1 — Encoder of Machine translation system. Part 1 has a brief explanation on the codes and the flow of tensors through the encoder. If you haven’t gone through Part 1…
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LLMs and Transformers from Scratch: the Decoder
As always, the code is available on our GitHub . One Big While Loop After describing the inner workings of the encoder in transformer architecture in our previous article , we shall see the next segme...
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Methods for Decoding Transformers
During text generation tasks, the crucial step of decoding bridges the gap between a model’s internal vector representation and the final human-readable text output. The selection of decoding strategi...
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Methods for Decoding Transformers
During text generation tasks, the crucial step of decoding bridges the gap between a model’s internal vector representation and the final human-readable text output. The selection of decoding strategi...
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The Encoder-Decoder Architecture
In general seq2seq problems like machine translation ( Section 10.5 ), inputs and outputs are of varying lengths that are unaligned. The standard approach to handling this sort of data is to design an...
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Transcribr
Digitizing handwritten documents to improve storage, access, search, and analysis is a compelling challenge. Prior to the deep learning revolution, no clear path existed towards achieving such a goal…...
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Encoders — How To Write Them, How To Use Them
In a perfect world, all programmers, scientists, data-engineers, analysts, and machine-learning engineers alike dream that all data could arrive at their doorstep in the cleanest form possible…
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Huffman Decoding
We already saw how to encode a given data using Huffman Encoding in Huffman Encoding & Python Implementation post. Now we will examine how to decode a Huffman Encoded data to obtain the initial…
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Transformer
A transformer model. User is able to modify the attributes as needed. The architecture is based on the paper “Attention Is All You Need”. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Ll...
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Simplifying Transformers: State of the Art NLP Using Words You Understand — part 5— Decoder and…
Simplifying Transformers: State of the Art NLP Using Words You Understand , Part 5: Decoder and Final Output The final part of the Transformer series Image from the original paper. This 4th part of t...
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➡️ Edge#45: Understanding Encoder-Decoder Architectures and Sequence-to-Sequence Learning
In this issue: we explore Encoder-Decoder Architectures; we learn how Amazon uses encoder-decoder to teach Alexa to chat more naturally; we explain Tf-seq2seq – a general-purpose, open-source encoder-...
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Target Encoding
Introduction Most of the techniques we've seen in this course have been for numerical features. The technique we'll look at in this lesson, *target encoding*, is instead meant for categorical feature...
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Joining the Transformer Encoder and Decoder Plus Masking
Last Updated on January 6, 2023 We have arrived at a point where we have implemented and tested the Transformer encoder and decoder separately, and we may now join the two together into a complete mod...
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Implementing the Transformer Decoder from Scratch in TensorFlow and Keras
Last Updated on January 6, 2023 There are many similarities between the Transformer encoder and decoder, such as their implementation of multi-head attention, layer normalization, and a fully connecte...
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TransformerEncoder
TransformerEncoder is a stack of N encoder layers. Users can build the BERT( https://arxiv.org/abs/1810.04805 ) model with corresponding parameters. encoder_layer – an instance of the TransformerEncod...
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Decode a lost language by code!
Languages are like people, they are born, they live, and they die. However, some languages die before their natural life-span because of some dominant languages. When the dominant languages become…
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A Guide to the Encoder-Decoder Model and the Attention Mechanism
Today, we’ll continue our journey through the world of NLP. In this article, we’re going to describe the basic architecture of an encoder-decoder model that we’ll apply to a neural machine…
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