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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
    11. 22621
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    Explanations

    words related to being wet or wet conditions

    oai_token-act-pair · gpt-3.5-turbo

    references to wet conditions or the concept of being wet

    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
    allery
    -0.73
    nesota
    -0.69
    osite
    -0.69
    uador
    -0.68
    vernment
    -0.67
    auri
    -0.66
    infeld
    -0.66
    udic
    -0.66
    士
    -0.66
     Kerr
    -0.65
    POSITIVE LOGITS
    ting
    1.10
     wet
    1.06
     Wet
    1.01
    ted
    0.99
    ter
    0.91
    ness
    0.89
     nood
    0.89
    ters
    0.87
    bike
    0.78
    lock
    0.78
    Activations Density 0.009%

    No Known Activations