Repository Index

State-of-the-Art Embeddings, Retrieval, and Reranking

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

• python
• search
• nlp
• semantic-search

Translated100+ Chinese Word Vectors

• chinese
• chinese-word-segmentation
• embeddings
• word-embeddings

Software in C and data files for the popular GloVe model for distributed word representations, a.k.a. word vectors or embeddings

Train and evaluate embeddings for similarity search with PyTorch. Includes contrastive losses, hard example mining, samplers, and retrieval metrics.

• metric-learning
• deep-learning
• computer-vision
• machine-learning

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

• chinese
• computer-vision
• multi-modal-learning
• nlp

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

• machine-learning
• convolutional-networks
• embedding-vectors
• embeddings

Fast State-of-the-Art Static Embeddings

• embeddings
• machine-learning
• model2vec
• nlp

Pre-trained word vectors of 30+ languages

• vector
• word2vec
• language
• fasttext

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

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

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

🦆 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

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

🚀 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

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

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