natural language processing with pytorch based on transformer model
-
Updated
Mar 25, 2020 - Jupyter Notebook
natural language processing with pytorch based on transformer model
A transformer-based model for automatic Image Captioning
Deep Learning Course Assignment on Image Captioning and Machine Translation using LSTMs
MoEL: Mixture of Empathetic Listeners
Implementation of the Swin Transformer in PyTorch.
Transformer Implementation using PyTorch for Neural Machine Translation (Korean to English)
Public repo for the paper: "COSMic: A Coherence-Aware Generation Metric for Image Descriptions" by Mert İnan, Piyush Sharma, Baber Khalid, Radu Soricut, Matthew Stone, Malihe Alikhani
# 自然语言处理 IMDB 情感分析数据集任务
pytorch Implementation of deep learning models
A Transformer Implementation that is easy to understand and customizable.
Pytorch implementation of image captioning using transformer-based model.
Pytorch implementation of image captioning using transformer-based model.
Pronunciation correction in vector quantized PPG representation space
PyTorch implementation of the original transformer, from scratch
NLP 领域常见任务的实现,包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断、三元组抽取、预训练模型等。
A research project in vision-based deep reinforcement learning centered on transfer learning, unsupervised representation learning, and applying attention mechanisms to interpret memories.
An encoder-transformer architecture-based framework for multi-variate time series prediction with a prognostics use case.
An EncoderTransformer Architecture developed from scratch using pytorch's neural network module as the base class. The developed model used for sentiment analysis and time series prediction tasks.
The project aims to utilize pre-trained Large Language Models (LLMs) for text summarization through diverse fine-tuning techniques. Comparative analysis with baseline RNN/LSTM language models is undertaken, utilizing established metrics such as Rouge score and BLEU.
古诗生成模型,基于Transformer/Chinese poetry geneation, based on transformer.
Add a description, image, and links to the transformer-pytorch topic page so that developers can more easily learn about it.
To associate your repository with the transformer-pytorch topic, visit your repo's landing page and select "manage topics."