git clone --recursive https://github.com/eladhoffer/seq2seq.pytorch cd seq2seq.pytorch; python setup.py develop Models Models currently available: Simple Seq2Seq recurrent model Recurrent Seq2Seq with attentiona
Seq2seq is a fast evolving field with new techniques and architectures being published frequently. The goal of this library is facilitating the development of such techniques and applications. While constantly improving the quality of code and documentation, we will focus on the following items: ...
seq2seq.py Repository files navigation README Apache-2.0 license 基于Pytorch的中文聊天机器人 集成BeamSearch算法 Pytorch 厉害了! Requirements: Python3 Pytorch Jieba分词 Pytorch 安装 python2.7 pip2 install http://download.pytorch.org/whl/cu80/torch-0.2.0.post3-cp27-cp27mu-manylinux1_x86_64.wh...
mini seq2seq Minimal Seq2Seq model with attention for neural machine translation in PyTorch. This implementation focuses on the following features: Modular structure to be used in other projects Minimal code for readability Full utilization of batches and GPU. ...
基于Tensorflow和Bahdanau注意力的另一个项目:https://github.com/dengxiuqi/Lyricist-tensorflow 方法 核心代码完全代码基于Pytorch 和 torchtext 采用Seq2Seq模型, 输入上句或歌名直接生成下句。反复将生成的下句输入网络, 循环往复, 可以得到整首歌曲 注意力机制使用的是Luong Attention, 在解码器生成下句的时候, ...
Seq2Seq(编码器+解码器)接口 Seq2Seq(编码器+解码器)代码实现 Seq2Seq模型训练 Seq2Seq模型推理 1.介绍 神经机器翻译(NMT)是一种机器翻译方法,它使用人工神经网络来预测一个单词序列的可能性,通常在一个单一的集成模型中建模整个句子。 对于计算机来说,用一个简单的基于规则的系统从一种语言转换成另一种语言是...
This code is written in PyTorch 0.2. By the time the PyTorch has released their 1.0 version, there are plenty of outstanding seq2seq learning packages built on PyTorch, such as OpenNMT, AllenNLP and etc. You can learn from their source code. ...
Asume your current work directory is "crnn_seq2seq_ocr_pytorch": #cd crnn_seq2seq_ocr.Pytorchpython3 inference.py --img_path ./data/test_img/20439171_260546633.jpg \ --encoder model/pretrained/encoder.pth --decoder model/pretrained/decoder.pth ...
model.load_state_dict(torch.load('tut1-model.pt')) test_loss = evaluate(model, test_iterator, criterion) print(f'| Test Loss: {test_loss:.3f}') 完整代码地址 https://github.com/kaimenluo/ailearning/blob/master/Pytorch_Seq2Seq/Seq2Seq.py...
安装本框架 pip install bert-seq2seq 安装pytorch 安装tqdm 可以用来显示进度条 pip install tqdm 运行 下载想训练的数据集,可以专门建个corpus文件夹存放。 使用roberta模型,模型和字典文件需要去 https://drive.google.com/file/d/1iNeYFhCBJWeUsIlnW_2K6SMwXkM4gLb_/view 这里下载。 具体可以参考这个github仓...