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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. 1-RES-JB
    11. 24000
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    Explanations

    phrases or commands prompting the user to input information or perform an action

    oai_token-act-pair · gpt-3.5-turbo

    commands or prompts for user input

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     coun
    -0.71
     laundering
    -0.67
    acca
    -0.67
     jud
    -0.65
    ector
    -0.62
     overr
    -0.61
     judgement
    -0.60
     fairness
    -0.58
    fml
    -0.58
     conviction
    -0.58
    POSITIVE LOGITS
    prise
    1.29
    prises
    1.26
    tain
    1.07
    tainment
    1.03
    taining
    1.03
    Enter
    1.03
    prising
    0.99
     Enter
    0.97
    tis
    0.87
    igible
    0.82
    Activations Density 0.006%

    No Known Activations