# 384-dimensional embedding
Fine Tune All MiniLM L6 V2
This is a model based on sentence-transformers that can map sentences and paragraphs to a 384-dimensional dense vector space, suitable for tasks such as clustering or semantic search.
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F
Madnesss
104
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Bios MiniLM
This is a model based on sentence-transformers that can map sentences and paragraphs to a 384-dimensional dense vector space, suitable for tasks such as clustering or semantic search.
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B
menadsa
15
0
Parameter Mini Lds
A patent parameter sentence recognition model based on all-MiniLM-L6-v2, which maps sentences and paragraphs into a 384-dimensional dense vector space, suitable for tasks like clustering or semantic search.
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P
nategro
14
0
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