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Gte Base Onnx

Developed by Qdrant
GTE-Base is a general-purpose text embedding model capable of converting text into high-dimensional vector representations, suitable for text classification and similarity search tasks.
Text Embedding
Transformers
Open Source License:Apache-2.0#Text Vectorization#Semantic Similarity#ONNX Optimization
Downloads 31
Release Time : 1/16/2024

Model Overview

This model is based on the Transformer architecture and can generate high-quality text embeddings, applicable in scenarios such as information retrieval, semantic search, and text classification.

Model Features

High-Quality Text Embeddings
Capable of generating high-quality text vector representations that capture semantic information.
Strong Generalization
Applicable to various natural language processing tasks, including text classification and similarity search.
ONNX Format
Provides an ONNX-converted version for easy deployment and use across different platforms.

Model Capabilities

Text Vectorization
Semantic Similarity Calculation
Text Classification
Information Retrieval

Use Cases

Information Retrieval
Document Search
Quickly retrieve relevant documents based on query semantics.
Improves search accuracy and recall rate.
Text Classification
Sentiment Analysis
Classify text based on sentiment orientation.
Recommendation Systems
Content Recommendation
Recommend related items based on content similarity.
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