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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. 2-RES-JB
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    Explanations

    phrases related to preventing or stopping negative events or outcomes

    oai_token-act-pair · gpt-3.5-turbo

    terms related to avoiding negative outcomes or preventing crises

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ammy
    -0.75
     Candy
    -0.70
    ONES
    -0.70
     Soda
    -0.69
    ession
    -0.69
    hops
    -0.67
     Resistance
    -0.67
    ingham
    -0.67
     Wine
    -0.66
    Cola
    -0.66
    POSITIVE LOGITS
     aver
    1.40
    uve
    0.98
     avert
    0.94
    ted
    0.93
    ting
    0.93
    tle
    0.89
    tering
    0.79
    ulence
    0.78
    wings
    0.75
    ters
    0.72
    Activations Density 0.008%

    No Known Activations