今天来推荐一本Transformers宝典《Transformers for Machine Learning》,它现在在亚马逊上卖140美元。 全书共有60多种Transformer架构的讲解,还有相关的知识和技巧,不管你是搞语音、文本、时间序列还是计算机视觉的,都能用得上。只要你有本科的基础知识,读起来就毫无压力!
BERT 在英语 NLP 任务上的成功激励了它在其他语言中的应用。然而,只有对于拥有足够大量无标签数据的语言,才能使用 BERT 的训练流程。这促使了多语言模型的发展,希望通过在多种语言上进行预训练,模型能够将高资源语言的核心 NLP 知识转移到低资源语言中,最终得到一个能够在多语言之间对齐表示的多语言模型。 本章涵盖...
关于Transformer的综合性书籍,市面上确实存在多本优秀的著作,它们从多个角度深入剖析了Transformer模型及其在不同领域的应用。以下是一些值得推荐的Transformer综合性书籍: 1. 《Transformers for Machine Learning》 内容概述:该书涵盖了60多个Transformer架构和对应的知识及技巧,涉及语音、文本、时间序列和计算机视觉等多个方...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. pythonnlpmachine-learningnatural-language-processingdeep-learningtensorflowpytorchtransformerspeech-recognitionseq2seqflaxpretrained-modelslanguage-modelsnlp-librarylanguage-modelhacktoberfestbertjaxpytorch-transformersmodel-hub ...
Everything depends on the final output layer for the network, but the basic structure of the transformer remains quite similar for any task. For this particular post, let’s take a closer look at the machine translation example. From a distance, the below image shows how the transformer looks...
We introduce Attention Free Transformer (AFT), an efficient variant of Transformers that eliminates the need for dot product self attention. In an AFT layer, the key and value are first combined with a set of learned position biases, the result of which is multiplied with the query in an el...
You can transfer some parameters from a small model to a large model (note: I sort & smooth them too), for faster and better convergence (see https://www.reddit.com/r/MachineLearning/comments/umq908/r_rwkvv2rnn_a_parallelizable_rnn_with/). My CUDA kernel: https://github.com/BlinkDL...
S VP NP ADJV deep learning is very powerful 7 7 多标签分类seq2seq 一个样本属于多个 类别 Class 1 Class 1 Class 3 Class 10 Class 3 Class 9 Class 17 Seq2seq Class 9 Class 7 Class 13 /abs/1909.03434 /abs/1707.05495 8 Seq2seq for Object Detection /abs/2005.12872 9 Seq2seq output ...
Advanced Deep Learning with Python, 2019 Transformers for Natural Language Processing, 2021 Papers Attention Is All You Need, 2017 Summary In this tutorial, you discovered how to run inference on the trained Transformer model for neural machine translation. Specifically, you learned: How to run in...
Variational Transformers for Diverse Response Generation.Zhaojiang Lin, Genta Indra Winata, Peng Xu, Zihan Liu, Pascale Fung[PDF] This code has been written using PyTorch >= 0.4.1. If you use any source codes or datasets included in this toolkit in your work, please cite the following paper...