Repository Index

A Toolkit for Industrial Topic Modeling

• topic-modeling
• topic-models
• lda
• sentence-lda

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

• community-detection
• graph-clustering
• deepwalk
• networkx

Fast State-of-the-Art Static Embeddings

• embeddings
• machine-learning
• model2vec
• nlp

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

• machine-learning
• knowledge-graph
• relational-learning
• representation-learning

The repository host gives no description.

🤖 A Python library for learning and evaluating knowledge graph embeddings

• knowledge-graph-embeddings
• knowledge-graphs
• machine-learning
• link-prediction

Sent2Vec encoder and training code from the paper "Skip-Thought Vectors"

Netease Youdao's open-source embedding and reranker models for RAG products.

WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval.

• embedding-models
• multimodal
• multimodal-llm

This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.

Code for 'LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders'

An Open-Source Package for Network Embedding (NE)

• network-embedding

🦆 Contextually-keyed word vectors

• spacy
• nlp
• natural-language-processing
• word2vec

A fast, efficient universal vector embedding utility package.

• python
• natural-language-processing
• nlp
• machine-learning

Tensorflow implementation of contextualized word representations from bi-directional language models

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

• word2vec
• text-mining
• natural-language-processing
• glove

🚀 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.

• nlp
• natural-language-processing
• artificial-intelligence
• embeddings

repository for Publicly Available Clinical BERT Embeddings

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

• deep-learning
• protein-sequences
• protein-structure
• semi-supervised-learning

A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.

Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.

• ai
• graphs
• synerise
• embeddings

Learning Heterogeneous Tactile Representation for General Dexterous Manipulation

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

• artificial-intelligence
• clip
• pathology
• vision-and-language

UCE is a zero-shot foundation model for single-cell gene expression data