1298 Open source projects that are alternatives of or similar to Embedding As Service

A fast, efficient universal vector embedding utility package.

finalfusion embeddings in Rust

🎨 🎨NLP 自然语言处理教程 🎨🎨 https://dataxujing.github.io/NLP-paper/

Fast word vectors with little memory usage in Python

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

Embedding模型代码和学习笔记总结

A small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.

Compact high quality word embeddings for Russian language

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

Persian sentiment analysis ( آناکاوی سهش های فارسی | تحلیل احساسات فارسی )

Visualize word embeddings of a vocabulary in TensorBoard, including the neighbors

兜哥出品 <一本开源的NLP入门书籍>

Exploring the simple sentence similarity measurements using word embeddings

cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information

Using pre trained word embeddings (Fasttext, Word2Vec)

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Deep Character CNN LSTM Encoder with Classification and Similarity Models

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

Sentiment analysis of tweets in Russian using Convolutional Neural Networks (CNN) with Word2Vec embeddings.

Google News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.

Sample code for training Word2Vec and FastText using wiki corpus and their pretrained word embedding..

Load embeddings and featurize your sentences.

Transformer implemented in Keras

Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.

A python package to run contextualized topic modeling. CTMs combine BERT with topic models to get coherent topics. Also supports multilingual tasks. Cross-lingual Zero-shot model published at EACL 2021.

Programming Assignments and Lectures for Stanford's CS 224: Natural Language Processing with Deep Learning

A data set and model for german sentiment classification.

Word Embeddings (e.g. Word2Vec) in Go!

Implementation of State-of-the-art Text Classification Models in Pytorch

Compute Sentence Embeddings Fast!

Sarcasm Detection for Sentiment Analysis

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019

nlp lecture-notes and source code

Read and use word2vec vectors in Go

Compass-aligned Distributional Embeddings. Align embeddings from different corpora

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)

TensorFlow implementation of word2vec applied on https://www.kaggle.com/tamber/steam-video-games dataset, using both CBOW and Skip-gram.

Multiple implementations for abstractive text summurization , using google colab

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

All about Neural Networks!

Service Classification based on Service Description

An Engine-Agnostic Deep Learning Framework in Java

An implementation of word2vec applied to [stanford philosophy encyclopedia](http://plato.stanford.edu/)

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

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

Code for "Effective Dimensionality Reduction for Word Embeddings".

NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager

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.

Fast vectorization, topic modeling, distances and GloVe word embeddings in R.

TextClf ：基于Pytorch/Sklearn的文本分类框架，包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型，通过简单配置即可完成数据处理、模型训练、测试等过程。

A curated list of awesome embedding models tutorials, projects and communities.

R wrapper for fastText

dna2vec: Consistent vector representations of variable-length k-mers

Implementation of Hierarchical Attention Networks in PyTorch

Creating word embeddings from scratch and visualize them on TensorBoard. Using trained embeddings in Keras.

Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.

Four word embedding models implemented in Python. Supporting arbitrary context features

Dict2vec is a framework to learn word embeddings using lexical dictionaries.