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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. 10688
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    Explanations

    background settings or contexts described in written text

    oai_token-act-pair · gpt-3.5-turbo

    references to visual backdrops or settings

    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
    ishable
    -0.88
    alties
    -0.81
    ldon
    -0.80
    secut
    -0.78
    nery
    -0.74
    ike
    -0.73
    cers
    -0.73
    ealing
    -0.72
    cer
    -0.71
    atri
    -0.70
    POSITIVE LOGITS
     backdrop
    1.39
    GROUND
    0.83
    enance
    0.75
    drops
    0.73
    ĸļ
    0.71
     EDITION
    0.68
     setting
    0.68
     Setting
    0.68
    )=(
    0.68
    FORE
    0.64
    Activations Density 0.008%

    No Known Activations