Visualization for simple attention and Google's multi-head attention.
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Updated
Mar 8, 2018 - Java
Visualization for simple attention and Google's multi-head attention.
Neat (Neural Attention) Vision, is a visualization tool for the attention mechanisms of deep-learning models for Natural Language Processing (NLP) tasks. (framework-agnostic)
attention mechanism in keras, like Dense and RNN...
Train and visualize Hierarchical Attention Networks
PyTorch implementation of the End-to-End Memory Network with attention layer vizualisation support.
Plot the vector graph of attention based text visualisation
Lightweight visualization tool for neural attention mechanisms
A Pytorch implementation of the paper 'Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering'
my codes for learning attention mechanism
Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.
Multimodal Bi-Transformers (MMBT) in Biomedical Text/Image Classification
Summary of Transformer applications for computer vision tasks.
(ECCV2020) Tensorflow implementation of A Generic Visualization Approach for Convolutional Neural Networks
Creating word-weighted heatmap's latex script given a list of tokens and attention scores
This project presents Attention-enhanced Multi-channel Recurrent Convolutional Network (AMRCN), for explainable fake news detection.
Transfer learning pretrained vision transformers for breast histopathology
Encoder-Decoder CNN-LSTM Model with an attention mechanism for image captioning. Trained using the Microsoft COCO Dataset.
Implemented image caption generation method propossed in Show, Attend, and Tell paper using the Fastai framework to describe the content of images. Achieved 24 BLEU score for Beam search size of 5. Designed a Web application for model deployment using the Flask framework.
Shopify-Pipedrive Integration This project provides a JavaScript program that integrates Shopify and Pipedrive, allowing you to automate the process of creating deals in Pipedrive based on Shopify orders. The program follows a series of steps to fetch data from Shopify and Pipedrive, create or update records, and establish connections between them.
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