contextual-embeddings

danlou/LMMS

Language Modelling Makes Sense - WSD (and more) with Contextual Embeddings

lunayach/visNER

In the wild extraction of entities that are found using Flair and displayed using a very elegant front-end.

KRR-Oxford/BERTMap

BERTMap: A BERT-Based Ontology Alignment System

hyintell/topicx

Model zoo for topic models, neural topic models, contextual embeddings for topic models ...

JasonYao81000/ADL2019

Applied Deep Learning (2019 Spring) @ NTU

iris2hu/diachronic-sense-modeling

seriousran/BERT-embedding

A simple wrapper class for extracting features(embedding) and comparing them using BERT in TensorFlow

anebz/eu-sim

Exploring semantic similarities between contextualized embeddings

honghanhh/ner-combining-contextual-and-global-features

[ICADL] Named entity recognition architecture combining contextual and global features

twitter-research/lmsoc

Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining

sunipa/On-Measuring-and-Mitigating-Biased-Inferences-of-Word-Embeddings

Debiasing both contextual and context free embeddings and developing a downstream metric for bias measurement

adithya8/ContextualEmbeddingDR

Empirical Comparison of Dimensionality Reduction Techniques for Contextual Embeddings over Low Sample Human-Level Tasks

ksipos/polysemy-assessment

Code and data for the paper 'Unsupervised Word Polysemy Quantification with Multiresolution Grids of Contextual Embeddings'

dr-irani/Quantifying-Bias-Contextualized-Embeddings

Semester project for Machine Learning: Deep Learning, Spring 2020

DrCBeatz/vajrayana-chat

Vajrayana AI Chat Web App (Python/Django/HTMX/OpenAI API). Create and converse with your own AI experts on Vajrayana Buddhism based on teachings from prominent Tibetan Tulkus and teachers.

heydarimo/Contextual-Embedding-Using-RNNs

Contextual embeddings assign each word a representation based on its context, thereby capturing uses of words across varied contexts and encoding knowledge that transfers across languages. in this repository we tend to implement this concept using Recurrent Neural Networks.

SiavashShams/Contextual-Embeddings-Using-HateBert-and-RNNs

We aim to clasify tweets based on three categories 0: hate, 1: offensive, 2: neutral. For this purpose we use HateBert pretrained model with RNNs as the trainable layers

tuananhfrtk/0-Combining-Contextual-words-and-KG-embeddings

Contextual embeddings are able to encode word meaning and polysemy to some degree. However, richer semantic information requires using representations other than texts, like knowledge graphs (KG). The goal of this project is to design a model to combining contextual and KG embeddings.

kyopark2014/contextual-embedding

It shows an analytic agent based on advanced RAG.

yunwoong7/text-embedding-toolkit

A powerful toolkit for text chunking and semantic search using OpenSearch. This toolkit provides various text chunking strategies and embedding capabilities for efficient document retrieval.