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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. 1-RES-JB
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    Explanations

    references to the city of San Francisco

    oai_token-act-pair · gpt-3.5-turbo

    references to San Francisco

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    lain
    -0.79
    pins
    -0.77
    gie
    -0.72
    taker
    -0.71
    igham
    -0.70
    utions
    -0.69
    ombo
    -0.69
    stall
    -0.68
    xual
    -0.68
    pin
    -0.67
    POSITIVE LOGITS
    SF
    1.20
     SF
    1.20
     Chronicle
    0.90
    ORTS
    0.90
    PB
    0.84
    PD
    0.82
    FF
    0.81
    WA
    0.80
    SD
    0.79
    DF
    0.79
    Activations Density 0.007%

    No Known Activations