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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. 7-RES-JB
    11. 8687
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    Explanations

    phrases related to expectations or intentions being met or not met

    oai_token-act-pair · gpt-3.5-turbo

    phrases expressing expectations or desires regarding outcomes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Pak
    -0.65
     Gul
    -0.64
     Pai
    -0.64
     Rush
    -0.64
     Panic
    -0.63
     Moss
    -0.62
     Stern
    -0.61
     coincidence
    -0.61
     surprise
    -0.60
     Vish
    -0.60
    POSITIVE LOGITS
    !.
    0.83
    ember
    0.81
    .—
    0.69
    illac
    0.69
    ault
    0.68
    .'
    0.67
    $.
    0.67
    zel
    0.67
    .'"
    0.65
    .","
    0.64
    Activations Density 0.235%

    No Known Activations