There are 13 repositories under embeddings topic.
100+ Chinese Word Vectors 上百种预训练中文词向量
A library for transfer learning by reusing parts of TensorFlow models.
Basic Utilities for PyTorch Natural Language Processing (NLP)
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
A python library for self-supervised learning on images.
A fast, efficient universal vector embedding utility package.
A curated list of awesome embedding models tutorials, projects and communities.
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN
Data augmentation for NLP, presented at EMNLP 2019
Pre-trained subword embeddings in 275 languages, based on Byte-Pair Encoding (BPE)
Implementation of triplet loss in TensorFlow
Solves basic Russian NLP tasks, API for lower level Natasha projects
Implementation of the node2vec algorithm.
A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
A tool for learning vector representations of words and entities from Wikipedia
A vector database for machine learning embeddings.
Library for faster pinned CPU <-> GPU transfer in Pytorch
Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
Curated List of Persian Natural Language Processing and Information Retrieval Tools and Resources
Named Entity Recognition using multilayered bidirectional LSTM
Compute Sentence Embeddings Fast!
Fuzzy string matching, grouping, and evaluation.
A framework that provides a simple API for developing ML-driven data processing and search pipelines.
Nimfa: Nonnegative matrix factorization in Python
Natural Language Processing Pipeline - Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging and Dependency Parsing
Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)
text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。
Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
Fast word vectors with little memory usage in Python
Recommender Systems Paperlist that I am interested in
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
Graph convolutional neural network for multirelational link prediction
Toolkit to help understand "what lies" in word embeddings. Also benchmarking!