huggingface/sentence-transformers

State-of-the-Art Embeddings, Retrieval, and Reranking

https://skillcdn.ai/gh/huggingface/sentence-transformers

내 AI에 이 주소를 연결하면 이 스킬들을 쓸 수 있어요. 연결 방법 보기

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기본 브랜치main
커밋4a3b5cd
라이선스Apache-2.0

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스킬과 문서의 원문에서 찾습니다. 화면용 번역은 검색되지 않아요.

This is a tool-neutral Agent Skill for training and fine-tuning sentence-transformers models. It covers model selection, hard-negative mining, loss / evaluator choice, training, evaluation, and Hub p…

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스킬

train-sentence-transformersTrain or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval, similarity, clustering, classification, paraphrase mining, dedup, multimodal), `CrossEncoder` (reranker, pair scoring for two-stage retrieval / pair classification), `SparseEncoder` (SPLADE, sparse embedding model for learned-sparse retrieval), and `MultiVectorEncoder` (ColBERT / late-interaction, per-token embeddings scored with MaxSim). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing. Use for any sentence-transformers training task.Apache-2.0