Encoder-only是以Bert为代表的模型及其衍生优化版本为主,那就以Bert为例来学习Encoder-only架构;BERT(Bidirectional Encoder Representations from Transformers)是一种在自然语言处理(NLP)领域引起巨大轰动的预训练语言模型,由Google于2018年提出。其核心原理是结合了Transformer架构和双向语言模
1 Transformer结构https://jalammar.github.io/illustrated-transformer/Transformer一个巨大的优点是:模型在处理序列输入时,可以对整个序列输入进行并行计算,不需要按照时间步循环递归处理输入序列。1.1 Transformer宏观结构Transformer可以看作是seq2seq模型的一种,对比之前的RNN,只是将Encode Transformer [ai笔记13] 大模型...
随着Transformer结构的出现,自然语言处理领域取得了突破。Transformer模型具有自注意力机制,可以有效地捕获输入序列中的长距离依赖关系和上下文信息。基于Transformer的编码器-解码器(Encoder-Decoder)架构成为主流,广泛应用于各种任务,包括机器翻译、文本摘要和对话生成等。 在此基础上,出现了Decoder-only架构。Decoder-only架构...
Decoder-onlyLess model parameters00–0199–00Multi-modal abstractive summarization for videos is an emerging task, aiming to integrate multi-modal and multi-source inputs (video, audio transcript) into a compressed textual summary. Although recent multi-encoder-decoder models on this task have shown...
Transformer-based Encoder-Decoder Models !pip install transformers==4.2.1 !pip install sentencepiece==0.1.95 Thetransformer-basedencoder-decoder model was introduced by Vaswani et al. in the famousAttention is all you need paperand is today thede-factostandard encoder-decoder architecture in natural...
主流开源大语言模型主要基于decoder-only架构或其变种,encoder-decoder架构仍待研究。 许多中文开源指令数据集是由ChatGPT生成或从英文翻译而来,存在版权和质量问题。 为填补这些空白,该工作: 采用了非对称的编码器-解码器架构(浅编码器,深解码器),融入UL2多任务训练、长度适应训练和双语Flan训练三个阶段。
这篇论文介绍了一种名为YOCO(You Only Cache Once)的新型解码器-解码器架构,旨在提高大型语言模型的推理效率和性能。 EMNLP2024投稿群建立! 论文:You Only Cache Once: Decoder-Decoder Architectures for Language Models 地址:https://arxiv.org/pdf/2405.05254 ...
It gives the attention layer multiple “representation subspaces”. As we’ll see next, with multi-headed attention we have not only one, but multiple sets of Query/Key/Value weight matrices (the Transformer uses eight attention heads, so we end up with eight sets for each encoder/decoder)....
We currently support the following transformer models. BERT[Python][C++] ALBERT[Python] Roberta[Python] Transformer Decoder[Python] GPT2[Python] Boost BERT Inference in 2 Lines of Python Code importtorchimporttransformersimportturbo_transformersif__name__=="__main__":turbo_transformers.set_num_thre...
The rise of decoder-only Transformer models written byShraddha Goled Apart from the various interesting features of this model, one feature that catches the attention is its decoder-only architecture. In fact, not just PaLM, some of the most popular and widely used language models are decoder-...