Sentence Transformers
Embedding, retrieval, and reranking framework for NLP tasks
Visit tool
sbert.net
About Sentence Transformers
Sentence Transformers is a framework for computing embeddings, retrieval, and reranking. It provides an easy method to compute embeddings using Sentence Transformer models, calculate similarity scores using Cross-Encoder models, or generate sparse embeddings using Sparse Encoder models.
Description summarised by AI from the sources listed below.
Key features
- embedding computation
- embedding
- embedding models
- reranker models
- retrieval
- reranking
- sparse encoder models
- sentence transformer models
- pre-trained models
- cross encoder models
- fine-tuning on custom data
- training and fine-tuning
Use cases
- semantic search
- semantic textual similarity
- paraphrase mining
Pricing
Pricing model: Unknown — we have not been able to confirm pricing from the official website, so nothing is stated here.
Pricing summarised by AI from the sources listed below.
