#1 LLM: Decoding LLM Transformer Architecture — Part 1
Mar 3, 2024 · Decoder: The decoder builds the final output step by step, using both the encoder’s clues and its own growing chain of words to figure out what comes next. It’s like completing a puzzle with...
Understanding Encoder And Decoder LLMs - Sebastian Raschka, …
Jun 17, 2023 · Delve into Transformer architectures: from the original encoder-decoder structure, to BERT & RoBERTa encoder-only models, to the GPT series focused on decoding. Explore their evolution, strengths, & applications in NLP tasks.
How LLMs Work ? Explained in 9 Steps — Transformer Architecture
Dec 24, 2023 · The transformer architecture is split into two distinct parts, the encoder and the decoder. These components work in conjunction with each other and they share a number of similarities.
A Gentle Introduction to Attention and Transformer Models
Mar 29, 2025 · The original transformer architecture is composed of an encoder and a decoder. Its layout is shown in the figure below. Recall that the transformer model was developed for translation tasks, replacing the seq2seq architecture that was commonly used with RNNs. Therefore, it borrowed the encoder-decoder architecture.
Visualizing and Explaining Transformer Models From the Ground …
Jan 19, 2023 · The Encoder-Decoder Concept. The Transformer model relies on the interactions between two separate, smaller models: the encoder and the decoder. The encoder receives the input, while the decoder outputs the prediction.
Transformer Architecture | LLM: From Zero to Hero
Feb 22, 2024 · Let’s run through the key ideas of the architecture when training a model. I drew a diagram to illustrate the training process of the GPT-like decoder-only transformer architecture: First, we require a sequence of input characters as training data. These inputs are converted into a vector embedding format.
Transformers and LLMs 11-785, Fall 2023 Shikhar Agnihotri 1 LiangzeLi. Part 1 Transformers 2. Transformers 3 • Tokenizaton • Input Embeddings • PositionEncodings • Residuals • Query • Key • Value • Add & Norm • Encoder • Decoder
LLMs and Transformers from Scratch: the Decoder
Jan 10, 2024 · In this article, we delve into the decoder component of the transformer architecture, focusing on its differences and similarities with the encoder. The decoder’s unique feature is its loop-like, iterative nature, which contrasts with the encoder’s linear processing.
Decoder-Based Large Language Models: A Complete Guide
Apr 27, 2024 · Decoder-based LLMs can be broadly classified into three main types: encoder-decoder, causal decoder, and prefix decoder. Each architecture type exhibits distinct attention patterns. Based on the vanilla Transformer model, the encoder-decoder architecture consists of two stacks: an encoder and a decoder.
Transformer Llm Diagram Overview | Restackio
Feb 23, 2025 · Encoder-Decoder Structure. The architecture consists of two main components: the encoder and the decoder. The encoder processes the input data, transforming it into a latent representation, while the decoder generates the output sequence from this representation.