原因1：过往研究证明decoder-only泛化化性能更好Google有两篇著名的发表于ICML’22的论文，一个是《Examining Scaling and Transfer of Language Model Architectures for Machine Translation》，另一个是《What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?》，两篇论文...
在我看来最目前的LLM基本使用Decoder only的原因就是：Decoder only 的单向注意力表达结构相较于Encoder-...
1. 在LLM发展得早期阶段,encoder-only和encoder-decoder模型更受欢迎。然而,自2021年起,随着游戏规则改变者GPT-3入局,decoder-only经历了显著的增长并逐渐主导LLMs的发展,于此同时在BERT带来的初期爆炸式增长之后,encoder-only模型逐渐开始淡出。 2. encoder-decoder模型仍具有前景,因为这种类型的架构仍在积极探索中,而...
Efficient encoder-decoder architecture for small language models (≤1B parameters) with cross-architecture knowledge distillation and vision-language capabilities encoder-decoder vision-and-language llm decoder-only Updated Feb 7, 2025 Python cisnlp / MEXA Star 10 Code Issues Pull requests 🔍 ...
Large language models (LLMs) have achieved remarkable success in the field of natural language processing, enabling better human-computer interaction using natural language. However, the seamless integration of speech signals into LLMs has not been explored well. The "decoder-only" architecture has ...
NVIDIA recently announced that NVIDIA TensorRT-LLM now accelerates encoder-decoder model architectures. TensorRT-LLM is an open-source library that optimizes inference for diverse model architectures, including the following: Decoder-only models, such as Llama 3.1 Mixture-of-experts (MoE) mo...
Meanwhile, if we perform fine-tuning, the model will also continue the sequence but only using the specific ground truths provided in the supervised learning phase. GPT-1 Implementation: Look-Ahead Mask & Positional Encoding As we already know the theory behind GPT-1, let’s now implement the...
Too Long; Didn't ReadThis section outlines how decoder-only transformers function in LLMs, detailing self-attention networks and the importance of keys/values caches for efficient inference. Addressing caching challenges is vital for improving performance in applications like machine translation and text...
Efficient encoder-decoder architecture for small language models (≤1B parameters) with cross-architecture knowledge distillation and vision-language capabilities Topics encoder-decoder vision-and-language llm decoder-only Resources Readme License MIT license Code of conduct Code of conduct Security...
In this article we prove that the general transformer neural model undergirding modern large language models (LLMs) is Turing complete under reasonable assumptions. This is the first work to directly address the Turing completeness of the underlying technology employed in GPT-x as past work has ...