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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. 9-RES-JB
    11. 1616
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    Explanations

    phrases related to cause and effect

    oai_token-act-pair · gpt-3.5-turbo

    themes related to cause-and-effect relationships

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    ounter
    -0.78
    rique
    -0.74
     [|
    -0.67
    oise
    -0.67
    emale
    -0.67
    ffect
    -0.66
     Citation
    -0.64
    ahime
    -0.64
    essor
    -0.64
    elsh
    -0.63
    POSITIVE LOGITS
     culmin
    0.97
     except
    0.84
     toget
    0.82
     culminated
    0.78
    together
    0.76
     together
    0.76
     neatly
    0.73
     begs
    0.73
     happening
    0.70
     combined
    0.70
    Activations Density 0.197%

    No Known Activations