Technology · Library
Sentence Transformers
Library · Catalog tech@1
Embeddings for sentences and text.
- Categories
- Matched as
- sbert
- sentence transformers
- sentence-transformers
Momentum
Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works
Momentum
Collecting0 of 5 signalsNo score yet. Momentum is published only when at least 2 of the 5 signals have history. Sentence Transformers has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.
Snapshot OCT 24, 2026 · Scoring tech@1
- Official repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.19,144 stars now
- Member repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.0 new members in 30 days
- Package adoption
- Not published by its registries
- Its packages’ registries publish no adoption figure, so there is nothing to grow.
- Open models
- Collecting
- Download growth needs Crest’s daily observations of its official models 30 days apart.278M downloads in 30 days · 27 official models
- News
- Collecting
- News counts once there are 3 events across the last 60 days; it has 1.0 in the last 30 days · 1 in the 30 before
Adoption by registry
The growth of Sentence Transformers’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.
No registry has two observations of Sentence Transformers’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.
News activity
- Events · 7 days
- 0published events that mention it
- Events · 30 days
- 0published events that mention it
- Previous 30 days
- 1events in the 30 days before
Momentum history
Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.
Repositories
Official 1
- huggingface/sentence-transformers
State-of-the-Art Embeddings, Retrieval, and Reranking
19.1K stars
Members 7repositories tagged with one of its aliases, most-starred first
- OpenBMB/UltraRAG
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
5.7K stars
- embeddings-benchmark/mteb
MTEB: State-of-the-art evaluation of embeddings across languages and modalities
3.4K stars
- ddangelov/Top2Vec
Top2Vec learns jointly embedded topic, document and word vectors.
3.1K stars
- beir-cellar/beir
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
2.3K stars
- MinishLab/model2vec
Fast State-of-the-Art Static Embeddings
2.2K stars
- Minima-AI-Inc/minima
On-premises conversational RAG with configurable containers
1K stars
- octimot/StoryToolkitAI
An editing tool that uses AI to transcribe, understand content and search for anything in your footage, integrated with ChatGPT and other AI models
1K stars
Packages
“Is” packages are Sentence Transformers itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.
Is 1the technology itself, most-adopted first
- sentence-transformers
Embeddings, Retrieval, and Reranking
Not published by PyPI
Ecosystem 42packages that depend on it, most-adopted first
- simba-core
Knowledge Management System that connects to your RAG system
Not published by PyPI - simplemem
Efficient Lifelong Memory for LLM Agents
Not published by PyPI - sirchmunk
Sirchmunk: From raw data to self-evolving real-time intelligence.
Not published by PyPI - sparrow-parse
Sparrow Parse is a Python package (part of Sparrow) for parsing and extracting information from documents.
Not published by PyPI - trustrag
RAG Framework within Reliable input,Trusted output
Not published by PyPI - uqlm
UQLM (Uncertainty Quantification for Language Models) is a Python package for UQ-based LLM hallucination detection.
Not published by PyPI
Models
Open models on Hugging Face. Official models are published under the prefixes the catalog declares; derivatives declare an official model as their base, and are never credited by name alone. Downloads are the Hub’s rolling 30-day count. All of them in the model list
Official 27the 12 most downloaded
- 193.4Mdownloads / 30 days
- 40.6Mdownloads / 30 days
- 17.9Mdownloads / 30 days
- 8.6Mdownloads / 30 days
- 2.7Mdownloads / 30 days
- 2.6Mdownloads / 30 days
- 1.5Mdownloads / 30 days
- 1.4Mdownloads / 30 days
- 1.4Mdownloads / 30 days
- 1.3Mdownloads / 30 days
- 857.1Kdownloads / 30 days
- 648.9Kdownloads / 30 days
Derivatives 7models in the catalog that declare an official model as their base
- 4.4Mdownloads / 30 days
- 281.1Kdownloads / 30 days
- 186.1Kdownloads / 30 days
- 141.3Kdownloads / 30 days
- 137.7Kdownloads / 30 days
- 136.7Kdownloads / 30 days
- 109Kdownloads / 30 days
Latest news the 2 latest events that mention it
- 59d agoAUG 26, 2026
- 2mo agoAUG 18, 2026