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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. 0-RES-JB
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    Explanations

    phrases with the word "wonders."

    oai_token-act-pair · gpt-3.5-turbo

    terms related to wonders, nature phenomena, and mountainous regions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     boiled
    -0.69
    bro
    -0.68
    actionDate
    -0.64
    skin
    -0.63
     usb
    -0.63
    sheet
    -0.63
    itched
    -0.63
    poly
    -0.60
    Code
    -0.60
     habitual
    -0.59
    POSITIVE LOGITS
     wonders
    2.85
     Mountains
    2.02
     Wonders
    1.40
     miracles
    1.04
     marvel
    0.95
    mount
    0.93
     Bridges
    0.91
     imag
    0.90
    anic
    0.89
    awatts
    0.87
    Activations Density 0.026%

    No Known Activations