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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. 4-RES-JB
    11. 6820
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    Explanations

    goals or objectives expressed in the text

    oai_token-act-pair · gpt-3.5-turbo

    mentions of objectives or targets

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

    No Comments

    Negative Logits
    ols
    -0.73
    CV
    -0.73
    BuyableInstoreAndOnline
    -0.71
    greg
    -0.69
    uggage
    -0.68
    Versions
    -0.67
    oute
    -0.67
    Luck
    -0.64
     Geological
    -0.63
    Python
    -0.63
    POSITIVE LOGITS
    posts
    0.96
     Goal
    0.88
    Goal
    0.83
    goal
    0.82
     kicker
    0.79
    lessly
    0.78
     goal
    0.76
    iste
    0.76
    yrim
    0.74
    ims
    0.73
    Activations Density 0.026%

    No Known Activations