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

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

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

[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

🦆 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

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.

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