There are 7 repositories under elmo topic.
Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation),etc. All codes are implemented intensorflow 2.0.
Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo
Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com
Keyphrase or Keyword Extraction 基于预训练模型的中文关键词抽取方法(论文SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-trained Language Model 的中文版代码)
BERT-NER (nert-bert) with google bert https://github.com/google-research.
NLP research:基于tensorflow的nlp深度学习项目,支持文本分类/句子匹配/序列标注/文本生成 四大任务
A list of pretrained Transformer models for the Russian language.
A short tutorial on Elmo training (Pre trained, Training on new data, Incremental training)
Keras Implementation of Aspect based Sentiment Analysis
Source code for "Head-Driven Phrase Structure Grammar Parsing on Penn Treebank" published at ACL 2019
Exploring the simple sentence similarity measurements using word embeddings
Cross-Lingual Alignment of Contextual Word Embeddings
A collection of resources on using BERT (https://arxiv.org/abs/1810.04805 ) and related Language Models in production environments.
A text classification example with Bert/ELMo/GloVe in pytorch
This repo contains all the notebooks mentioned in blog.
Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015
Simple library to work with pre-trained ELMo models in TensorFlow
torch tutorial and paper implementation mainly about NLP
:art: :art:NLP 自然语言处理教程 :art::art: https://dataxujing.github.io/NLP-paper/
This is a german ELMo deep contextualized word representation. It is trained on a special German Wikipedia Text Corpus.
Applied Deep Learning (2019 Spring) @ NTU
Source code for ACL 2020 paper "Learning Spoken Language Representations with Neural Lattice Language Modeling"
A Deep Learning-Based Approach for Named Entity Recognition on Commercial Receipts
Fair quantitative comparison of NLP embeddings from GloVe to RoBERTa with Sequential Bayesian Optimization fine-tuning using Flair and SentEval. Extension of HyperOpt library to log_b priors.
Useful Stata routines
Multi-Label Text Classification with Transfer Learning
TensorFlow code and pre-trained models for A Dynamic Word Representation Model Based on Deep Context. It combines the idea of BERT model and ELMo's deep context word representation.
BiLSTM-CRF model for NER
Visualizing ELMo Contextual Vectors for Word Sense Disambiguation