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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 2-RES-JB
    6. 326
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    Explanations

    the brand name "Hilton."

    oai_token-act-pair · gpt-4-turbo

    references to locations or entities with the word "Hilton" in them

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the Hilton brand

    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
    */(
    -0.88
     redistributed
    -0.75
    anwhile
    -0.75
    FTWARE
    -0.71
    period
    -0.71
    atically
    -0.68
     Izan
    -0.67
    reenshots
    -0.66
    umbnail
    -0.66
    osion
    -0.65
    POSITIVE LOGITS
     Hilton
    1.14
     Hotel
    0.97
     Marriott
    0.89
     Coliseum
    0.87
    sburg
    0.86
     hotels
    0.76
     Plaza
    0.73
     hotel
    0.73
    655
    0.73
    ilton
    0.69
    Activations Density 0.003%

    No Known Activations