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CIKM2023_SubspaceEmbedding

Pluggable Embedding Code of our CIKM paper titled "Lightweight Adaptation of Neural Language Models via Subspace Embedding"

Subspace Embedding

  • Embedding layer can be customised.
  • Follow the parameters detail in the paper to reproduce the subspace of the embedding.
  • Practically, the training/inference speed is similar with Embedding layer.

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Pluggable Embedding Code for our CIKM paper titled "Lightweight Adaptation of Neural Language Models via Subspace Embedding"

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