bge micro This is a sentence transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. It is distilled from bge small en v1.5, with 1/4 the non embedding parameters. It has 1/2 the parameters of the smallest commonly used embedding model, all MiniLM L6 v2, with similar performance. Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling operation on top of the contextualized word embeddings. Evaluation Results For an automated evaluation of this model, see the Sentence Embeddings Benchmark : https://seb.sbert.net Full Model Architecture Citing & Authors
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy