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Chonky Modernbert Base 1

Developed by mirth
Chonky is a Transformer model that intelligently splits text into meaningful semantic chunks for RAG systems.
Downloads 221
Release Time : 4/14/2025

Model Overview

This model processes text and divides it into semantically coherent segments, which can be used as input for embedding-based retrieval systems or language models in RAG workflows.

Model Features

Semantic Chunking
Intelligently splits text into meaningful semantic chunks while maintaining coherence
Long Sequence Support
Based on ModernBERT architecture, natively supports sequences up to 8192 tokens
RAG Optimization
Designed specifically for RAG (Retrieval-Augmented Generation) systems, optimizing chunk quality

Model Capabilities

Text Segmentation
Semantic Analysis
Paragraph Division

Use Cases

Information Retrieval
RAG System Preprocessing
Prepares semantically coherent text chunks for retrieval-augmented generation systems
Improves retrieval efficiency and relevance
Text Processing
Document Chunking
Splits long documents into meaningful paragraphs
Facilitates subsequent processing and analysis
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