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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. 7-RES-JB
    11. 7316
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    Explanations

    references to lack of awareness or insight, specifically related to blind spots or blindness

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    xit
    -0.94
    ICAN
    -0.72
    ALLY
    -0.69
     accur
    -0.68
    afort
    -0.68
    akeru
    -0.67
     Occupations
    -0.67
    CE
    -0.63
    ickr
    -0.62
    OPLE
    -0.62
    POSITIVE LOGITS
    sight
    1.37
    sided
    1.29
    fold
    1.28
    blind
    1.07
    eyed
    0.99
    sighted
    0.98
    ingly
    0.97
    eye
    0.93
    legged
    0.92
    ibility
    0.92
    Activations Density 0.035%

    No Known Activations