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NSIO_NeuralSearchIndexingOptimization

Optimizing the Differentiable Search Index (DSI) with data augmentation (Num2Word, Stopwords Removal, POS-MLM) and parameter-efficient fine-tuning (LoRA, QLoRA, AdaLoRA, ConvoLoRA), improving retrieval accuracy and efficiency while reducing memory and computational overhead. Evaluated on the MS MARCO dataset for scalable performance.

  • Updated Apr 3, 2025
  • Jupyter Notebook

Elixir port of HuggingFace's PEFT (Parameter-Efficient Fine-Tuning) library. Implements LoRA, AdaLoRA, IA3, prefix tuning, prompt tuning, and 30+ state-of-the-art PEFT methods for efficient neural network adaptation. Built for the BEAM ecosystem with native Nx/Axon integration.

  • Updated Jan 1, 2026
  • Jupyter Notebook

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