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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. 18206
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    Explanations

    terms related to significant entities, events or activities such as big business, big names, and big money

    oai_token-act-pair · gpt-3.5-turbo

    terms related to large corporations and influential entities

    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
     Ramos
    -0.61
     inquest
    -0.60
     masse
    -0.60
     plight
    -0.59
     Loft
    -0.58
     NTS
    -0.58
     psychiatrist
    -0.58
     Phill
    -0.58
     DG
    -0.57
     Plague
    -0.57
    POSITIVE LOGITS
    ————————
    0.79
    Thumbnail
    0.79
     (>
    0.77
    Winner
    0.75
    buster
    0.73
    ————
    0.71
    leground
    0.68
    ountain
    0.68
    Wan
    0.68
    RET
    0.68
    Activations Density 0.422%

    No Known Activations