Frpile GPL Test Pipeline All Mpnet Base V2 14000
This is a model based on sentence-transformers that maps sentences and paragraphs into a 768-dimensional dense vector space, suitable for tasks such as clustering or semantic search.
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Release Time : 9/11/2023
Model Overview
This model is primarily used to calculate semantic similarity between sentences and paragraphs by converting text into high-dimensional vector representations, supporting various natural language processing tasks.
Model Features
High-dimensional Vector Representation
Maps sentences and paragraphs into a 768-dimensional dense vector space
Semantic Similarity Calculation
Accurately calculates semantic similarity between different texts
Versatile Applications
Supports various natural language processing tasks such as clustering and semantic search
Model Capabilities
Sentence Embedding
Semantic Similarity Calculation
Text Clustering
Semantic Search
Use Cases
Information Retrieval
Semantic Search
Uses vector similarity to achieve more accurate search results than keyword matching
Improves the relevance of search results
Text Analysis
Document Clustering
Automatically groups documents based on semantic similarity
Discovers thematic structures within document collections
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