Deep Learning based Machine translation Models
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Updated
May 8, 2018 - Python
Deep Learning based Machine translation Models
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Transfer Learning Large Scale Transformers for Fact Checking
Examples for using transformer model in Pytorch
Final Project for ESE 546: Principles of Deep Learning
Vietnamese Wikipedia Paraphase Identity experiments
Extremely simple and understandable GPT2 implementation with minor tweaks
Easily deploy a state-of-the-art language model from HuggingFace's Transformers
A PyTorch implementation of BERT proposed by Devlin et al.
This project uses BERT(Bidirectional Encoder Representations from Transformers) for Yelp-5 fine-grained sentiment analysis. It also explores various custom loss functions for regression based approaches of fine-grained sentiment analysis.
Transfer Learning for Text Summarization
search engine based on feature extracted on pretrained transformerXL.
A repository to finetune transformers on a multilabel classification task ( based on transformers library ).
It is about how to load and aggregate pretrained word embeddings in pytorch, e.g., ELMo\BERT\XLNET.
NLP Service to perform text classification. This is the first part of Project Jarvis. This service integrates to the chat-bot service
Implementations of a variety of machine learning stuff
Exploration of BERT-BiLSTM models with Layer Aggregation (attention-based and capsule-routing-based) and Hidden-State Aggregation (attention-based and capsule-routing-based).
OOD Generalization and Detection (ACL 2020)
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