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# Semantic Retrieval Optimization
E5 Base
MIT
E5-base is a general-purpose text embedding model suitable for various natural language processing tasks such as classification, retrieval, clustering, and semantic similarity calculation.
Text Embedding English
E
intfloat
30.85k
20
Instructor Xl
Apache-2.0
Instructor is an instruction-tuned text embedding model capable of generating customized text embedding vectors for any task and domain without additional fine-tuning.
Text Embedding
Transformers English
Transformers EnglishI
hkunlp
149.36k
566
HPD MiniLM F128
Apache-2.0
A sentence representation model for semantic retrieval compressed via homomorphic projection distillation, with only 23 million parameters and a model size of 87MB
Text Embedding Transformers
TransformersH
Xuandong
13
0
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