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Install this package:

emerge -a sci-ml/sentence-transformers

Package Information

Description:

Sentence-Transformers (SBERT) provides sentence, image, and code embeddings via Transformer networks for semantic search, clustering, semantic textual similarity, and retrieval-augmented generation. Bundled training utilities support fine-tuning on contrastive losses; bundled inference utilities cover bi-encoders, cross- encoders (rerankers), and sparse encoders. Embedding-based RAG pipelines downstream — including sci-ml/amd-gaia's ui module and most LLM-orchestration frameworks — depend on this library.

Homepage:

https://www.SBERT.net https://github.com/huggingface/sentence-transformers https://pypi.org/project/sentence-transformers/

License:

Apache-2.0

Versions

Metadata

Description

• Sentence-Transformers (SBERT) provides sentence, image, and code embeddings via Transformer networks for semantic search, clustering, semantic textual similarity, and retrieval-augmented generation. Bundled training utilities support fine-tuning on contrastive losses; bundled inference utilities cover bi-encoders, cross- encoders (rerankers), and sparse encoders. Embedding-based RAG pipelines downstream — including sci-ml/amd-gaia's ui module and most LLM-orchestration frameworks — depend on this library.

Maintainers

• Ivan S. Titov (iohann.s.titov@gmail.com) - Type: person

Upstream

• Remote IDs:
  • github: huggingface/sentence-transformers
  • pypi: sentence-transformers

<pkgmetadata>
	<maintainer type="person">
		<email>iohann.s.titov@gmail.com</email>
		<name>Ivan S. Titov</name>
	</maintainer>
	<longdescription lang="en">
    Sentence-Transformers (SBERT) provides sentence, image, and code
    embeddings via Transformer networks for semantic search, clustering,
    semantic textual similarity, and retrieval-augmented generation.
    Bundled training utilities support fine-tuning on contrastive
    losses; bundled inference utilities cover bi-encoders, cross-
    encoders (rerankers), and sparse encoders. Embedding-based RAG
    pipelines downstream — including sci-ml/amd-gaia's ui module and
    most LLM-orchestration frameworks — depend on this library.
  </longdescription>
	<upstream>
		<remote-id type="github">huggingface/sentence-transformers</remote-id>
		<remote-id type="pypi">sentence-transformers</remote-id>
	</upstream>
</pkgmetadata>

Lint Warnings

• [Error] Missing md5-cache for ebuild sentence-transformers-5.5.1
• [Error] Missing md5-cache for ebuild sentence-transformers-5.5.0

Manifest