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Interpret and control dense embedding via sparse autoencoder.

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Embedding Scope

Table of Contents

Getting Started

  1. Install Conda:

    If Conda isn't installed, download it here.

    Conda is required to manage dependencies and ensure a consistent environment.

  2. Create Environment:

    conda env create -f environment.yml
  3. Activate Environment:

    conda activate scope
  4. Configure Workspace:

    To configure the workspace where the datasets and trained checkpoints are stored, update the source/__init__.py file with the desired path.

    For example:

    from pathlib import Path
    
    workspace = Path("/your/path/to/workspace")
    workspace.mkdir(mode=0o770, parents=True, exist_ok=True)

You're all set to begin!

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Interpret and control dense embedding via sparse autoencoder.

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