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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. 4-RES-JB
    11. 19423
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    Explanations

    quantitative terms or concepts

    oai_token-act-pair · gpt-3.5-turbo

    terms related to quantitative analysis

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    HOME
    -0.84
    lihood
    -0.76
     spare
    -0.68
    ãĥĩãĤ£
    -0.66
     Mansion
    -0.62
     Sutherland
    -0.62
     Archdemon
    -0.62
     Marcos
    -0.60
     Slayer
    -0.60
     dear
    -0.59
    POSITIVE LOGITS
    itatively
    1.46
     quant
    1.07
    itative
    1.00
    imet
    0.96
    idian
    0.96
    ifiable
    0.91
    izations
    0.86
    ifies
    0.85
    ified
    0.82
    tarians
    0.82
    Activations Density 0.009%

    No Known Activations