论文:Language Models are Unsupervised Multitask Learners 链接:cdn.openai.com/better-l GPT-2延续了GPT-1的架构,推出了四个不同规模的版本。从Small到XL版本,模型规模逐步扩大:Small版本与GPT-1相近,有12层解码块;Medium版本接近BERT-Large,有24层解码块;Large版本有36层解码块;
1.更加高效。相比encoder-decoder架构，decoder-only架构不需要预先编码输入序列，因此可以减少模型中需要处...
在当今的人工智能和自然语言处理(NLP)领域,大语言模型(Large Language Models, LLMs)如GPT系列已成为研究热点,并展现出强大的语言理解和生成能力。这些模型的一个显著特点是它们大多采用Decoder-only架构,而非传统的Encoder-Decoder或Encoder-Only架构。那么,为何Decoder-only架构会在大语言模型中占据主导地位呢?本文将深...
近年来,大型语言模型(Large Language Models,LLM)在自然语言处理领域取得了显著的进展。这些模型基于深度学习技术,通过对大量文本数据进行训练,能够理解和生成人类语言。然而,细心观察可以发现,现在的大语言模型基本上都是Decoder-only的架构。那么,为什么会出现这种情况呢?本文将重点探讨这个话题,并介绍Decoder-only架构的...
Large Language Models (LLMs) have demonstrated impressive capabilities in various tasks, including Multiple-Choice Question Answering (MCQA) evaluated on benchmark datasets with few-shot prompting. Given the absence of benchmark Science, Technology, Engineering, and Mathematics (STEM) datasets on ...
最近的大模型几乎一边倒地全是decoder-only架构,但实际上2019年发布的T5模型(encoder-decoder架构)表现已经非常不错了,人们可能忽略了这点。这篇文章 INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models O网页链接 给出了详细对比和讨论:1. Flan-T5击败了所有对手,包括基于LLama的Alp...
论文:You Only Cache Once: Decoder-Decoder Architectures for Language Models 地址:https://arxiv.org/pdf/2405.05254 摘要 介绍: YOCO是一种新型的大型语言模型架构,它通过仅缓存一次键值对(KV pairs)来显著降低GPU内存需求,同时保持全局注意力(global attention)能力。
Recently, zero-shot image captioning has gained increasing attention, where only text data is available for training.The remarkable progress in text-to-ima... J Luo,J Chen,Y Li,... - European Conference on Computer Vision 被引量: 0发表: 2025年 Vision-Language Consistency Guided Multi-modal...
and draw connections to prior models. We adapt contemporary classification networks (AlexNet, the VGG net, and GoogLeNet) into fully convolutional networks and transfer their learned representations by fine-tuning to the segmentation task. We then define a skip architecture that combines semantic informa...
The decoder has both those layers, but between them is an attention layer that helps the decoder focus on relevant parts of the input sentence (similar what attention does inseq2seq models). Bringing The Tensors Into The Picture Now that we’ve seen the major components of the model, let...