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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. 3-RES-JB
    11. 6122
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    Explanations

    words related to a large amount of activity or events happening in a short period of time

    oai_token-act-pair · gpt-3.5-turbo

    terms associated with intense activity or chaos

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    arers
    -0.88
    arer
    -0.81
    ĻĤ
    -0.74
    acted
    -0.72
    ACTED
    -0.71
    ©¶æ
    -0.68
    gemony
    -0.68
     dearly
    -0.67
    inav
    -0.64
    anium
    -0.64
    POSITIVE LOGITS
     flurry
    0.99
    cffff
    0.92
    naire
    0.88
    pread
    0.85
    cade
    0.83
     frenzy
    0.83
    storms
    0.80
     earthqu
    0.78
    storm
    0.77
    Timeout
    0.74
    Activations Density 0.018%

    No Known Activations