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Implementation of the Swin Transformer in PyTorch.
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。
Transformer Implementation using PyTorch for Neural Machine Translation (Korean to English)
Pytorch implementation of image captioning using transformer-based model.
Transformer-based model for Speech Emotion Recognition(SER) - implemented by Pytorch
:sparkles: Solve multi_dimensional multiple knapsack problem using state_of_the_art Reinforcement Learning Algorithms and transformers
natural language processing with pytorch based on transformer model
A Transformer Implementation that is easy to understand and customizable.
Pronunciation correction in vector quantized PPG representation space
pytorch Implementation of deep learning models
A research project in vision-based deep reinforcement learning centered on transfer learning, unsupervised representation learning, and applying attention mechanisms to interpret memories.
A transformer-based model for automatic Image Captioning
An encoder-transformer architecture-based framework for multi-variate time series prediction with a prognostics use case.
PyTorch implementation of the original transformer, from scratch
Magic The GPT - GPT inspired model to generate Magic the Gathering cards
# 自然语言处理 IMDB 情感分析数据集任务
古诗生成模型,基于Transformer/Chinese poetry geneation, based on transformer.
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.
Deep Learning Course Assignment on Image Captioning and Machine Translation using LSTMs
Pytorch implementation of image captioning using transformer-based model.
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.