Sentence Transformers Python Packages

mteb

MTEB: Massive Text Embedding Benchmark

model2vec

Fast State-of-the-Art Static Embeddings

setfit

Efficient few-shot learning with Sentence Transformers

beir

A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

top2vec

Top2Vec learns jointly embedded topic, document and word vectors.

fast-sentence-transformers

Simply, faster, sentence-transformers

spacy-sentence-bert

Sentence transformers models for SpaCy

smartmemo

Semantic memory and caching for LLM agents with classifier-validated equivalence instead of naive cosine thresholds.

chainmem

ChainMem（链忆）— 链式 + 向量混合记忆系统，让 AI 拥有像人一样的联想式回忆

classy-classification

This repository contains an easy and intuitive approach to few-shot classification using sentence-transformers or spaCy models, or zero-shot classification with Huggingface.

easy-transformers

Utility functions to work with transformers

semaclust

clustering similar strings using sentence embeddings and agglomerative clustering

factlens

Geometric LLM hallucination detection. No second LLM. Deterministic. Auditable.

open-text-embeddings

Open Source Text Embedding Models with OpenAI Compatible API

modern-bert-score

Re-implementation of BERTScore for evaluation of generated text, leveraging vLLM and SentenceTransformers.

hierarchy-transformers

Language Models as Hierarchy Encoders

embeddingcache

Retrieve text embeddings, but cache them locally if we have already computed them.

rk-transformers

Export and Run Hugging Face Transformers Models on Rockchip NPUs

tokenpack-rag

TokenPack packs long documents, codebases, PDFs, and folders into compact, evidence-dense LLM context using local embeddings, evidence scoring, and budget-aware selection.

context-lens

Semantic search knowledge base for MCP-enabled AI assistants. Index local files or GitHub repos, query with natural language. Built on LanceDB vector storage. Works with Claude Desktop, Cursor, and other MCP clients.

loremem-ai

Persistent memory for AI agents. Grammar-based extraction, 7-channel adaptive retrieval, local-first. pip install loremem-ai

semantic-keywords

TF-IDF counts words. semantic-keywords understands meaning. It uses sentence embeddings (all-MiniLM-L6-v2 by default) and Maximal Marginal Relevance (MMR) to return keywords that are both relevant and diverse — not just the most frequent phrases. Works fully offline after a one-time model download. No API key. No rate limits.

schema-matching

Using XGboost and Sentence-Transformers to perform schema matching task on tables.

splade-index

An ultra-fast search index for SPLADE sparse neural retrieval models.