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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
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    Explanations

    mentions of the city of San Francisco

    oai_token-act-pair · gpt-3.5-turbo

    mentions of San Francisco

    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
    mble
    -0.83
    big
    -0.70
    respons
    -0.69
    ym
    -0.68
    draw
    -0.67
    meaning
    -0.66
    ilater
    -0.65
    sch
    -0.65
     Beir
    -0.62
    åĤ
    -0.61
    POSITIVE LOGITS
     Francisco
    1.18
     Bay
    1.00
     Examiner
    0.99
     Rican
    0.91
     Chronicle
    0.89
     County
    0.82
     Diego
    0.81
     Rico
    0.80
     Giants
    0.80
     Lumpur
    0.78
    Activations Density 0.013%

    No Known Activations