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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. 15485
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    INDEX
    Explanations

    keywords related to importance, central focus, or vital points

    oai_token-act-pair · gpt-3.5-turbo

    terms associated with central or key elements within various contexts

    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
    resso
    -0.80
    atson
    -0.71
    eem
    -0.71
    ammy
    -0.70
     Ibid
    -0.68
    odcast
    -0.66
    ECH
    -0.66
    utics
    -0.64
     Odyssey
    -0.64
    ursed
    -0.63
    POSITIVE LOGITS
     focal
    1.13
    rament
    0.76
     bou
    0.72
     flare
    0.71
    ="#
    0.71
    rang
    0.70
    imation
    0.70
    istics
    0.70
     flares
    0.69
     attraction
    0.68
    Activations Density 0.012%

    No Known Activations