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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. 9-RES-JB
    11. 10200
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    Explanations

    phrases indicating a large or significant quantity or amount

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating quantity or amount

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    çīĪ
    -0.80
    Ħ¢
    -0.76
    farious
    -0.74
    irie
    -0.68
    Ń·
    -0.67
    rador
    -0.67
    displayText
    -0.66
    rir
    -0.66
    wcsstore
    -0.66
    oche
    -0.65
    POSITIVE LOGITS
     accomplishment
    1.01
     compared
    1.00
     achievement
    0.95
     odds
    0.93
     considering
    0.93
     exaggeration
    0.90
     margin
    0.84
     understatement
    0.82
     (~
    0.82
     feat
    0.82
    Activations Density 0.241%

    No Known Activations