Chatbot using Tensorflow (Model is transformer) ko
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Updated
Dec 10, 2018 - Python
Chatbot using Tensorflow (Model is transformer) ko
Joint text classification on multiple levels with multiple labels, using a multi-head attention mechanism to wire two prediction tasks together.
Machine Translation models (with and without attention) to convert sentences in Tamil to Hindi. Transformer models are also used for this same task and performance is compared.
An experimental project for autonomous vehicle driving perception with steering angle prediction and semantic segmentation using a combination of UNet, attention and transformers.
This is implementation of famous multi head attention mode for conversational ai paper. This model is trained on both Cornell movie data set and WikkiQna data set provided by microsoft
A Transformer Encoder where the embedding size can be down-sized.
list of efficient attention modules
This package is a Tensorflow2/Keras implementation for Graph Attention Network embeddings and also provides a Trainable layer for Multihead Graph Attention.
Synthesizer Self-Attention is a very recent alternative to causal self-attention that has potential benefits by removing this dot product.
A Faster Pytorch Implementation of Multi-Head Self-Attention
Implementation of "Attention is All You Need" paper
A PyTorch Implementation of PGL-SUM from "Combining Global and Local Attention with Positional Encoding for Video Summarization", Proc. IEEE ISM 2021
A repository for implementations of attention mechanism by PyTorch.
This repository contains the code for the paper "Attention Is All You Need" i.e The Transformer.
The implementation of transformer as presented in the paper "Attention is all you need" from scratch.
Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.
Very simple implementation of GPT architecture using PyTorch and Jupyter.
PyTorch implementation of the Transformer architecture from the paper Attention is All You Need. Includes implementation of attention mechanism.
3D Printing Extrusion Detection using Multi-Head Attention Model
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