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Frpile GPL Test Pipeline BAAI Bge Large En 14000

Developed by DragosGorduza
This is a model based on sentence-transformers that can map sentences and paragraphs into a 1024-dimensional dense vector space, suitable for tasks such as clustering or semantic search.
Downloads 14
Release Time : 9/11/2023

Model Overview

This model is primarily used for vectorized representation of sentences and paragraphs, capable of generating high-quality semantic embedding vectors, suitable for similarity calculation and information retrieval tasks in natural language processing.

Model Features

High-dimensional Vector Representation
Capable of mapping sentences and paragraphs into a 1024-dimensional dense vector space, capturing rich semantic information.
Semantic Similarity Calculation
The generated vectors can be used to accurately calculate semantic similarity between sentences.
Easy Integration
Can be easily integrated into existing applications through the sentence-transformers library.

Model Capabilities

Sentence vectorization
Semantic similarity calculation
Text clustering
Information retrieval

Use Cases

Information Retrieval
Document Similarity Search
Using the vectors generated by the model for document similarity search to improve retrieval accuracy.
Can more accurately find semantically similar documents
Text Analysis
Text Clustering
Automatic clustering analysis of large volumes of text.
Can group texts based on semantic similarity
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