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Indosbert Large

Developed by denaya
indoSBERT-large is an Indonesian sentence embedding model based on sentence-transformers, which maps sentences and paragraphs into a 256-dimensional vector space, suitable for tasks such as clustering and semantic search.
Downloads 510
Release Time : 7/27/2023

Model Overview

This model is a modified version of indobert-large-p1, fine-tuned using a Siamese network approach, specifically designed to provide meaningful semantic embeddings for Indonesian sentences.

Model Features

Indonesian-specific
Sentence embedding model specifically optimized for Indonesian language
High-dimensional semantic space
Maps sentences into a 256-dimensional dense vector space
Siamese network architecture
Fine-tuned using a Siamese network approach inspired by SBERT

Model Capabilities

Sentence embedding
Semantic similarity calculation
Text clustering
Semantic search

Use Cases

Information retrieval
Similar document retrieval
Find semantically similar documents in an Indonesian document repository
Text analysis
Text clustering
Automatic semantic-based classification of Indonesian texts
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