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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 9-RES-JB
    11. 22762
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    INDEX
    Explanations

    numbers representing quantities or measurements

    oai_token-act-pair · gpt-3.5-turbo

    quantitative values, particularly numbers and their magnitudes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     downside
    -0.64
     menace
    -0.62
    redit
    -0.59
     promise
    -0.57
     Mohamed
    -0.56
    Redditor
    -0.56
     sofa
    -0.56
     stigma
    -0.55
    raf
    -0.55
     label
    -0.54
    POSITIVE LOGITS
     directions
    1.07
     increments
    1.03
     places
    1.01
     locations
    0.96
     languages
    0.95
     minutes
    0.94
     respects
    0.92
     contexts
    0.92
     categories
    0.89
     seconds
    0.88
    Activations Density 0.104%

    No Known Activations