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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. 8329
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    Explanations

    instances where someone is impressed by something

    oai_token-act-pair · gpt-3.5-turbo

    expressions of admiration or being impressed

    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
    ©¶æ
    -0.80
    andro
    -0.71
    rama
    -0.70
    atra
    -0.70
    race
    -0.66
    nown
    -0.66
    interrupted
    -0.65
    ignty
    -0.64
    stitial
    -0.63
    rigan
    -0.63
    POSITIVE LOGITS
     impressed
    0.84
    mented
    0.82
    sson
    0.74
     resemb
    0.71
    ulously
    0.70
    Magikarp
    0.67
    ments
    0.67
    MENTS
    0.66
    oresc
    0.64
    uates
    0.63
    Activations Density 0.014%

    No Known Activations