H

Hindi Sentence Similarity Sbert

Developed by l3cube-pune
This is a Hindi sentence similarity model fine-tuned on the STS dataset, supporting semantic similarity calculation between Hindi sentences.
Downloads 655
Release Time : 11/5/2022

Model Overview

This model is fine-tuned from the HindSBERT model for sentence similarity tasks, capable of mapping Hindi sentences into a 768-dimensional vector space for calculating semantic similarity between sentences.

Model Features

Hindi Optimization
Specially optimized for Hindi text, better handling the semantic features of Hindi sentences.
Sentence Similarity Calculation
Accurately calculates semantic similarity between Hindi sentences, suitable for applications like information retrieval and Q&A systems.
768-dimensional Vector Representation
Converts sentences into 768-dimensional dense vector representations, facilitating subsequent similarity calculations and clustering analysis.

Model Capabilities

Sentence Embedding
Semantic Similarity Calculation
Text Feature Extraction

Use Cases

Information Retrieval
Similar Document Retrieval
Find semantically similar documents or paragraphs based on query sentences.
Improves the relevance of retrieval results.
Q&A Systems
Question Matching
Match user questions with similar questions in the knowledge base.
Improves the accuracy of Q&A systems.
Text Clustering
Document Clustering
Cluster documents based on sentence vectors.
Identifies topic distributions in text data.
Featured Recommended AI Models
┬й 2025AIbase