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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    9. 2-RES-JB
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    Explanations

    the word "catch" in different contexts

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "catch" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    xual
    -0.82
     reluct
    -0.74
     millenn
    -0.73
     prosec
    -0.73
    htar
    -0.70
     oversaw
    -0.70
    uilt
    -0.70
     contem
    -0.68
    urred
    -0.68
     administ
    -0.67
    POSITIVE LOGITS
    phrase
    0.96
    aways
    0.86
    ãĤ¤
    0.85
    backs
    0.83
    catch
    0.82
    bowl
    0.81
    weight
    0.79
    ãĥĥãĥī
    0.78
    ãĤ¤ãĥĪ
    0.76
     Tackle
    0.75
    Activations Density 0.009%

    No Known Activations