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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. 13258
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    INDEX
    Explanations

    the word "ach" with a high activation value

    oai_token-act-pair · gpt-3.5-turbo

    the concept of achieving or accomplishment

    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
    ©¶æ
    -0.74
    drm
    -0.70
     kindly
    -0.69
    fml
    -0.67
    ĸļ
    -0.67
     CBO
    -0.65
     futures
    -0.64
    PLA
    -0.64
    senal
    -0.63
    ¥ŀ
    -0.63
    POSITIVE LOGITS
    annel
    1.07
    akra
    1.04
    iev
    1.02
    idon
    1.00
    ieving
    1.00
    ach
    0.96
    rome
    0.93
    mann
    0.92
    ten
    0.89
    lear
    0.87
    Activations Density 0.015%

    No Known Activations