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All MiniLM L2 V2

Developed by tabularisai
This model is distilled from all-MiniLM-L12-v2, achieving nearly 2x faster inference speed while maintaining high accuracy on both CPU and GPU.
Downloads 5,063
Release Time : 5/5/2025

Model Overview

An efficient text embedding model suitable for tasks like sentence similarity calculation and retrieval-augmented generation.

Model Features

High-speed inference
Nearly 2x faster inference speed compared to the all-MiniLM-L6-v2 model
High accuracy
Maintains accuracy close to the original model while achieving faster inference
Lightweight
Compact model size, suitable for resource-constrained environments

Model Capabilities

Text embedding
Sentence similarity calculation
Semantic retrieval

Use Cases

Information retrieval
Retrieval-augmented generation (RAG)
Used as a retriever in RAG pipelines to quickly find relevant documents
Improves retrieval speed and system response time
Semantic analysis
Sentence similarity calculation
Calculates semantic similarity between two sentences
Applicable in scenarios like Q&A systems and duplicate detection
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