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Nystromformer 4096
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Nystromformer 4096

Developed by uw-madison
Long-sequence Nyströmformer model trained on WikiText-103 v1 dataset, supports sequence processing up to 4096 tokens
Large Language Model
Transformers
#Long Sequence Processing#Efficient Attention Mechanism#WikiText Pretraining
Downloads 74
Release Time : 4/18/2022

Model Overview

A Transformer variant using Nyström approximation method, specialized in efficient long-sequence text processing by reducing self-attention complexity

Model Features

Long Sequence Processing
Supports input sequences up to 4096 tokens, overcoming traditional Transformer's context length limitations
Efficient Attention Mechanism
Uses Nyström method to approximate self-attention computation, significantly reducing O(n²) complexity
Memory Optimization
Reduces memory usage through low-rank approximation of attention matrices

Model Capabilities

Long-text language modeling
Context-aware text generation
Document-level semantic understanding

Use Cases

Text Generation
Long Document Auto-completion
Generates coherent subsequent text based on long context
Maintains long-distance semantic consistency
Language Model Research
Long-sequence Modeling Benchmark
Evaluates model performance in capturing long-range dependencies
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