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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. 3-RES-JB
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    Explanations

    references to wolves in the text

    oai_token-act-pair · gpt-3.5-turbo

    mentions of wolves or wolf-related terms

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    NAS
    -0.85
    claimed
    -0.71
    thritis
    -0.67
    angan
    -0.67
    Downloadha
    -0.66
    ulty
    -0.66
    graded
    -0.66
    metics
    -0.65
    arters
    -0.64
    office
    -0.64
    POSITIVE LOGITS
     wolves
    1.13
     wolf
    1.08
    hound
    1.03
     Fenrir
    0.99
    gang
    0.96
    wolves
    0.91
    enstein
    0.89
     Wolf
    0.79
    Wolf
    0.78
    bats
    0.77
    Activations Density 0.005%

    No Known Activations