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Nystromformer 2048
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Nystromformer 2048
Developed by uw-madison
Nystromformer model trained on the WikiText-103 dataset, supporting long sequence processing (2048 tokens)
Downloads 38
Release Time : 4/18/2022
Model Overview
A Transformer variant using the Nyström method to approximate self-attention, suitable for long text sequence processing tasks
Model Features
Long Sequence Processing
Supports context lengths of 2048 tokens, suitable for processing long documents
Efficient Attention Mechanism
Uses the Nyström method to reduce the computational complexity of standard self-attention
Memory Optimization
Reduces memory consumption compared to standard Transformers, suitable for longer sequences
Model Capabilities
Text Generation
Language Modeling
Long Text Understanding
Use Cases
Text Generation
Long Document Continuation
Automatically generates coherent long-form text based on preceding context
Long text output with consistent context
Language Modeling
Text Probability Evaluation
Calculates the likelihood probability of text sequences
Can be used for text quality assessment or anomaly detection
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