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Modernbert Large Msmarco Bpr

Developed by BlackBeenie
This is a sentence-transformers model fine-tuned from ModernBERT-large, designed to map sentences and paragraphs into a 1024-dimensional dense vector space, supporting tasks such as semantic textual similarity and semantic search.
Downloads 21
Release Time : 2/7/2025

Model Overview

This model is fine-tuned based on the ModernBERT-large architecture, specifically designed for vector representations of sentences and paragraphs, suitable for various natural language processing tasks.

Model Features

Long Text Processing Capability
Supports sequences up to 8192 tokens in length, making it suitable for processing long documents and paragraphs.
Efficient Vector Representation
Maps text into a 1024-dimensional dense vector space, preserving rich semantic information.
Fine-tuning Optimization
Specially fine-tuned based on the ModernBERT-large architecture, optimizing performance for sentence similarity tasks.

Model Capabilities

Semantic Textual Similarity Calculation
Semantic Search
Paraphrase Mining
Text Classification
Text Clustering

Use Cases

Information Retrieval
Relevant Document Retrieval
Find semantically similar relevant document passages based on query sentences
Effectively matches semantically related but differently phrased text content
Question Answering Systems
Answer Passage Matching
Match user questions with candidate answer passages based on similarity
Accurately identifies the most relevant answer passages to the questions
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