Configurable Encoder-Decoder Sequence-to-Sequence model. Built with TensorFlow.

Very simple example of Seq2Seq model

Repo for Mincall - MinION basecaller we're working on during academic year 2016/2017.

Fine tuned Urdu to English machine translation pre train model using Hugging-Face Trainer API on custom dataset.

A new seq2seq model for fast training.

Testing out different seq2seq models in TensorFlow, and an implementation of a neural transducer.

A tensorflow 2.0 implementation with keras

Chatbot using Seq2Seq model using Tensorflow

Realistic Chatbot based on NLP & TensorFlow

Build A task oriented conversational model using seq2seq approaches approaches : without-Attention, with-Attention, with-Transfer Learning

include many sub-algorithms for the field of NLP

使用SequenceToSequence实现的简单聊天机器人

Seq2Seq model that restores punctuation on English input text.

Implementation of Neural Machine Translation from Spanish to English

Recurrent Neural Networks and their fun little usage

A Seq2Seq model for Tensorflow 2.0 and a few Tensorflow/Keras Seq2Seq model experiments.

Introduction nmt-chatbot is the implementation of chatbot using NMT - Neural Machine Translation (seq2seq). Includes BPE/WPM-like tokenizator (own implementation). Main purpose of that project is to make an NMT chatbot, but it's fully compatible with NMT and still can be used for sentence translations between two languages.

Successfully developed a text summarization model using Seq2Seq with attention to condense multi-turn dialogues from the SAMSum dataset into coherent and informative summaries.

Successfully developed a news summarization model using a Seq2Seq architecture with attention mechanism to generate concise and contextually accurate summaries from long-form news articles.

Successfully developed a dialogue summarization model using a Seq2Seq architecture with Attention on the DialogSum dataset to generate concise and coherent summaries of multi-turn conversations.