Papers › A Length-Extrapolatable Transformer

A Length-Extrapolatable Transformer

20 Dec 2022arXiv:2212.10554archive 2025-07-28

Yutao Sun, Li Dong, Barun Patra, Shuming Ma, Shaohan Huang, Alon Benhaim, Vishrav Chaudhary, Xia Song, Furu Wei

Position modeling plays a critical role in Transformers. In this paper, we focus on length extrapolation, i.e., training on short texts while evaluating longer sequences. We define attention resolution as an indicator of extrapolation. Then we propose two designs to improve the above metric of Transformers. Specifically, we introduce a relative position embedding to explicitly maximize attention resolution. Moreover, we use blockwise causal attention during inference for better resolution. We evaluate different Transformer variants with language modeling. Experimental results show that our model achieves strong performance in both interpolation and extrapolation settings. The code will be available at https://aka.ms/LeX-Transformer.

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Code

Syntology Ran 3 of 6 code samples harvested from 2 repositories linked to this paper; 3 have no recorded run. Of those that ran: 1 ran · honoured contract; 2 ran · violated contract.

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microsoft/torchscale officialmentioned in papermentioned on GitHubpytorch report
abacusai/long-context mentioned on GitHubpytorchApache-2.0 report
conceptofmind/palm mentioned on GitHubpytorchMIT report
fkodom/yet-another-retnet mentioned on GitHubpytorch report
lucidrains/rotary-embedding-torch mentioned on GitHubpytorch report

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1ran · honoured contract
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broadcat lucidrains/rotary-embedding-torch/rotary_embedding_torch/rotary_embedding_torch.py community (archive-listed) ran · honoured contract MIT (permissive) · 602eaf39ebc4c9ce · report
build_dataloaders conceptofmind/palm/palm/build_dataloaders.py community (archive-listed) unverified MIT (permissive) · a45309570f26c6bf · report
get_lr_scheduler_with_warmup conceptofmind/palm/train_distributed_hf.py community (archive-listed) unverified MIT (permissive) · 5b28d67e43c816eb · report
main conceptofmind/palm/build_dataset.py community (archive-listed) unverified MIT (permissive) · a7ae63aa96bbc8af · report
default identical code first harvested elsewhere ran · violated contract fingerprinted licence of this copy not recorded · 60fff7c3c400d7ff · report
exists identical code first harvested elsewhere ran · violated contract licence of this copy not recorded · aa5486a3650902d8 · report

Tasks

Language ModelingLanguage Modelling

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Methods

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

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