Repository Index

Topic Modelling for Humans

• gensim
• topic-modeling
• information-retrieval
• machine-learning

A very simple framework for state-of-the-art Natural Language Processing (NLP)

• pytorch
• nlp
• named-entity-recognition
• sequence-labeling

Retrieval and Retrieval-augmented LLMs

• embeddings
• information-retrieval
• llm
• sentence-embeddings

Postgres with GPUs for ML/AI apps.

• ml
• machine-learning
• ai
• ann

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

Translatedtext2vec, text to vector. A text vector representation tool that converts text into vector matrices. It implements text representation and text similarity calculation models such as Word2Vec, RankBM25, Sentence-BERT, and CoSENT, and works out of the box.

• similarity
• nlp
• text-similarity
• text2vec

Representation learning on large graphs using stochastic graph convolutions.

[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

• nlp
• sentence-embeddings

Open-source inference server and production cluster for all the models your agent needs.

• embeddings
• vector-search
• data-pipeline
• deep-learning

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

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

Siamese and triplet networks with online pair/triplet mining in PyTorch

• machine-learning
• deep-learning
• siamese-network
• triplet-loss

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

• colpali
• information-retrieval
• retrieval-augmented-generation
• vision-language-model

Easily compute clip embeddings and build a clip retrieval system with them

• semantic-search
• deep-learning
• multimodal
• ai

[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings

• embeddings
• information-retrieval
• language-model
• text-classification

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.

🦆 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.

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