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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. 2-RES-JB
    11. 576
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    Explanations

    brand and proper nouns related to technology, and historically significant locations associated with tragedy

    oai_token-act-pair · gpt-4-turbo

    proper nouns such as brand names and locations

    oai_token-act-pair · gpt-3.5-turbo

    references to specific brands, companies, and historical events

    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
    hood
    -0.93
    aneous
    -0.79
    aries
    -0.74
    dden
    -0.73
    robe
    -0.72
    estamp
    -0.72
    pton
    -0.71
    ricular
    -0.71
    ned
    -0.71
    cipled
    -0.71
    POSITIVE LOGITS
     Sach
    0.94
    ansas
    0.92
    chwitz
    0.90
    illary
    0.76
    iewicz
    0.74
    geist
    0.72
    hab
    0.71
    avorite
    0.70
    uve
    0.69
     Osw
    0.69
    Activations Density 0.027%

    No Known Activations