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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 15166
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    INDEX
    Explanations

    adjectives describing steepness or difficulty

    oai_token-act-pair · gpt-3.5-turbo

    descriptors of steepness or difficulty

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ignty
    -0.79
    uve
    -0.71
     IMAGES
    -0.71
    uter
    -0.70
    umbn
    -0.69
    gdala
    -0.69
    ubb
    -0.67
     Holo
    -0.65
     Smy
    -0.62
    bers
    -0.62
    POSITIVE LOGITS
     slopes
    1.12
    ly
    1.08
     slope
    1.08
    ened
    1.05
    ening
    1.03
     climb
    0.96
     gradient
    0.93
     uphill
    0.91
     ascent
    0.87
    nesses
    0.86
    Activations Density 0.054%

    No Known Activations