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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. 6-RES-JB
    11. 23816
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    Explanations

    words related to setting and achieving objectives or targets

    oai_token-act-pair · gpt-3.5-turbo

    references to specific objectives or goals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    oute
    -0.79
    ols
    -0.68
    ateur
    -0.67
    Luck
    -0.67
    avi
    -0.67
    CV
    -0.66
    uggage
    -0.66
    oqu
    -0.64
    BuyableInstoreAndOnline
    -0.63
    Versions
    -0.61
    POSITIVE LOGITS
    posts
    1.08
     Goal
    0.86
    Goal
    0.82
    goal
    0.77
    hetical
    0.76
    lessly
    0.76
    ims
    0.75
    post
    0.72
     accomplished
    0.71
     goal
    0.70
    Activations Density 0.038%

    No Known Activations