SoftwareFramework

Sentence Transformers

Sentence Transformers is a framework maintained by Hugging Face1 3. Its source code is public1 under the Apache License 2.02 5.

Sentence Transformers is a Python framework for using and training embedding and reranker models. It computes dense embeddings with Sentence Transformer models, scores text pairs with Cross-Encoder (reranker) models, and also supports sparse encoders and multi-vector models for ColBERT-style late-interaction retrieval, with pretrained models published on Hugging Face. Version 6.1.0 was released on September 18, 2026.1 4Fact reviewed Oct 8, 2026

Repository: Repository (external site: github.com)
Documentation: Documentation (SBERT.net) (external site: sbert.net)
License: LICENSE (Apache-2.0) (external site: github.com)
Website: Package on PyPI (external site: pypi.org)
Release notes: Releases (external site: github.com)

Last reviewedOct 8, 2026Entry updated Oct 8, 2026Documented release Unknown

Availability and license

Overall availability

Public

Source is public on GitHub, and the package is published on PyPI and conda-forge.1 6

Availability fact review: Oct 8, 2026

Availability is separate from permission: read the license before using or redistributing.

Apache License 2.0 (external site: github.com)2 5
Applies to: Code · SPDX Apache-2.0 · on the rubric’s OSI-approved software-license list · fact reviewed Oct 8, 2026
Plain-language guide to the Apache License 2.0

The repository is licensed under Apache 2.0 with a NOTICE file crediting the UKP Lab at TU Darmstadt (2019 to 2025) and Hugging Face, Inc. (2025 onward). Pretrained models loaded through the library carry their own licenses, which this record does not cover.2 3 1Fact reviewed Oct 8, 2026

Component reuse rights

A readable or downloadable component is not automatically reusable. These indicators concern recorded license evidence, not system certification.

weights: Unknown — no complete fact-level rights review
code: Reviewed qualifying license recorded — check scope and conditions
data: Unknown — no complete fact-level rights review
documentation: Unknown — no complete fact-level rights review

No complete system-rights review is recorded for this release.

Public materials checklist

Items for a framework under USASI rubric v0.2. Unknown means unassessed or insufficient evidence.

Public materials checklist for Sentence Transformers
Item	Status	Notes and evidence
Source codeIs the source code publicly readable?	Public	Public on GitHub, with example applications in the repository.1
DocumentationIs user documentation published?	Public	SBERT.net has a quickstart, installation guide, training overviews for each model type, and a package reference.1 6
InstallationAre installation instructions or packages publicly available?	Public	Installable with pip, uv, or conda-forge, or from source; optional extras add image, audio, video, training, ONNX, and OpenVINO support. Requires Python 3.10 or later, PyTorch 2.2 or later, and Transformers v5 or later.6 5
Supported platformsAre supported operating systems or hardware documented?	Partial	The package metadata lists Python 3.10 to 3.13. For GPU use the documentation defers to PyTorch's installation instructions; no operating system list is given.5 6
Release statusAre versioned releases published?	Public	Versioned GitHub releases with notes and matching PyPI versions, marked "Production/Stable"; 6.1.0 was released on 2026-09-18.4 5

What it is useful for

Semantic search, semantic textual similarity, paraphrase mining, and reranking, and training or fine-tuning embedding, reranker, sparse, and multi-vector models. Google's EmbeddingGemma 2 model card documents inference through this library.1 8Fact reviewed Oct 8, 2026

Organization context

Hugging Face

People: Nils Reimers

Provenance and derivatives

Sentence Transformers was originally developed by the UKP Lab at TU Darmstadt, a German university lab, and is now maintained in Hugging Face's GitHub organization.1 3

In the news

Dated, sourced updates in this catalog's news that mention this entry.

Aug 18, 2026 · Release
Sentence Transformers 6.0.0 adds MultiVectorEncoder for ColBERT-style late-interaction models
Sentence Transformers version 6.0.0 was published on GitHub on August 18, 2026. The release notes describe it as a major release that introduces Multi-Vector Embedding models, also known as late-interaction or ColBERT-style models, as a fourth model type, MultiVectorEncoder, alongside SentenceTransformer, CrossEncoder, and SparseEncoder. The notes say PyLate and Stanford-NLP ColBERT checkpoints load directly into it, that the dependency floor moves to transformers v5, and that the release contains breaking changes covered in a migration guide. USASI has not tested this release.
- Hugging Face
- Sentence Transformers

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S.-governed project

Two-organization history. The project was originally developed by the UKP Lab at TU Darmstadt in Germany, which the NOTICE file lists as copyright holder for 2019 to 2025. The repository is now in Hugging Face's GitHub organization, the NOTICE file lists Hugging Face, Inc. as copyright holder from 2025, and the README names a Hugging Face maintainer. Hugging Face, Inc. is a Delaware corporation per Hugging Face's terms of service; the catalog's hugging-face record assesses its U.S. headquarters. The catalog treats Hugging Face as the current maintaining entity.1 3 7

Assessed Oct 8, 2026

Sources

1.
huggingface/sentence-transformers README (external site: raw.githubusercontent.com)
Hugging Face (GitHub) · Repository · accessed Oct 8, 2026
2.
huggingface/sentence-transformers LICENSE (Apache-2.0) (external site: raw.githubusercontent.com)
Hugging Face (GitHub) · License · accessed Oct 8, 2026
3.
huggingface/sentence-transformers NOTICE.txt (external site: raw.githubusercontent.com)
Hugging Face (GitHub) · License · accessed Oct 8, 2026
4.
huggingface/sentence-transformers releases (GitHub API) (external site: api.github.com)
GitHub · Release notes · accessed Oct 8, 2026
5.
sentence-transformers package metadata (PyPI JSON API) (external site: pypi.org)
Python Package Index · Repository · accessed Oct 8, 2026
6.
Sentence Transformers installation (external site: sbert.net)
Sentence Transformers (SBERT.net) · Documentation · accessed Oct 8, 2026
7.
Hugging Face Terms of Service (external site: huggingface.co)
Hugging Face · Official page · accessed Oct 8, 2026
8.
google/embeddinggemma-2 model card (external site: huggingface.co)
Google DeepMind (via Hugging Face) · Model card · accessed Oct 8, 2026

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Cite this page

APA style

USASI. (2026, October 8). Sentence Transformers. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/sentence-transformers/

BibTeX

@misc{usasi_sentence_transformers,
  author = {{USASI}},
  title = {Sentence Transformers},
  year = {2026},
  month = oct,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/sentence-transformers/}},
  note = {United States of America Superintelligence. Last updated 2026-10-08}
}

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