1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.
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Updated
Sep 25, 2021 - C++
1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.
高质量中文预训练模型集合:最先进大模型、最快小模型、相似度专门模型
Train and Infer Powerful Sentence Embeddings with AnglE | 🔥 SOTA on STS and MTEB Leaderboard
😎 A curated list of awesome practical Metric Learning and its applications
3rd Place Solution for HomeDepot Product Search Results Relevance Competition on Kaggle.
Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.
🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
all kinds of baseline models for sentence similarity 句子对语义相似度模型
NLP for human. A fast and easy-to-use natural language processing (NLP) toolkit, satisfying your imagination about NLP.
an easy-to-use interface to fine-tuned BERT models for computing semantic similarity in clinical and web text. that's it.
Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
HyperTag - Intuitive Knowledge Management WebApp & CLI for Humans using Deep Learning & Tags
Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.
😷 Disease Ontology Semantic and Enrichment analysis
Dict2vec is a framework to learn word embeddings using lexical dictionaries.
Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text.
Emacs package that helps org-mode users (re)discover similar documents
STriP Net: Semantic Similarity of Scientific Papers (S3P) Network
A Python library to chunk/group your texts based on semantic similarity.
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