SentenceTransformers Documentation — Sentence Transformers …
Sentence Transformers (a.k.a. SBERT) is the go-to Python module for accessing, using, and training state-of-the-art embedding and reranker models. It can be used to compute …
Pretrained Models — Sentence Transformers documentation
We provide various pre-trained Sentence Transformers models via our Sentence Transformers Hugging Face organization. Additionally, over 6,000 community Sentence Transformers …
Quickstart — Sentence Transformers documentation - SBERT.net
Generally provides superior performance compared to a Sentence Transformer (a.k.a. bi-encoder) model. Often slower than a Sentence Transformer model, as it requires computation for each …
SentenceTransformer — Sentence Transformers documentation
Deprecated training method from before Sentence Transformers v3.0, it is recommended to use sentence_transformers.trainer.SentenceTransformerTrainer instead. This method should only …
Installation — Sentence Transformers documentation
These commands will link the new sentence-transformers folder and your Python library paths, such that this folder will be used when importing sentence-transformers.
Usage — Sentence Transformers documentation - SBERT.net
Usage Characteristics of Sentence Transformer (a.k.a bi-encoder) models: Calculates a fixed-size vector representation (embedding) given texts or images. Embedding calculation is often …
Training Overview — Sentence Transformers documentation
Most Sentence Transformer models use the Transformer and Pooling modules. The former loads a pretrained transformer model (e.g. BERT, RoBERTa, DistilBERT, ModernBERT, etc.) and …
Sentence Transformers: Multilingual Sentence, Paragraph, and …
Sentence Transformers: Multilingual Sentence, Paragraph, and Image Embeddings using BERT & Co. This framework provides an easy method to compute dense vector representations for …
Semantic Textual Similarity — Sentence Transformers …
Sentence Transformers implements two methods to calculate the similarity between embeddings: SentenceTransformer.similarity: Calculates the similarity between all pairs of embeddings.
util — Sentence Transformers documentation - SBERT.net
This function uses a SentenceTransformer model to embed the sentences in the dataset, and then finds the closest matches to each anchor sentence in the dataset. It then samples …