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Gte Large Onnx
GTE-Large is a text embedding model ported to ONNX, suitable for text classification and similarity search tasks.
Downloads 597
Release Time : 1/16/2024
Model Overview
GTE-Large is a high-performance text embedding model capable of converting text into high-dimensional vector representations, suitable for tasks such as text classification, similarity search, and information retrieval.
Model Features
High-Performance Text Embedding
Capable of generating high-quality text vector representations for various natural language processing tasks.
ONNX Format
The model has been converted to ONNX format for easy deployment and inference across different platforms.
Multilingual Support
Supports text processing in multiple languages (specific supported languages not specified).
Model Capabilities
Text Vectorization
Text Similarity Calculation
Text Classification
Information Retrieval
Use Cases
Information Retrieval
Document Similarity Search
Quickly find similar documents by comparing text vectors.
Improves search accuracy and efficiency
Text Classification
Sentiment Analysis
Use text vectors for sentiment classification.
Accurately identifies text sentiment tendencies
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