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Tct Colbert V2 Msmarco
TCT-ColBERT-V2 is a dense retrieval model based on knowledge distillation, which improves retrieval efficiency and quality through tightly coupled teacher mechanisms and batch negative optimization training.
Downloads 2,220
Release Time : 3/2/2022
Model Overview
This model is a variant of the ColBERT model, focusing on dense retrieval tasks, and optimizes retrieval performance through knowledge distillation techniques, making it suitable for large-scale document retrieval scenarios.
Model Features
Knowledge Distillation
Optimizes training through tightly coupled teacher mechanisms and batch negatives, enhancing the model's retrieval performance.
Efficient Retrieval
Employs dense retrieval technology, significantly improving the efficiency of large-scale document retrieval.
Batch Negative Optimization
Uses batch negatives during training to enhance the model's discriminative ability.
Model Capabilities
Document Retrieval
Dense Vector Representation
Large-scale Text Processing
Use Cases
Information Retrieval
Academic Literature Retrieval
Used for quickly retrieving relevant academic literature to improve research efficiency.
Performs excellently on multiple benchmark datasets with high retrieval accuracy.
Business Document Retrieval
Suitable for efficient retrieval and management of internal corporate documents.
Significantly improves document retrieval speed and accuracy.
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