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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. 20266
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    Explanations

    words related to sharp objects or concepts

    oai_token-act-pair · gpt-3.5-turbo

    words or phrases related to sharpness or intensity

    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
    pty
    -0.77
    ORED
    -0.71
     Dare
    -0.69
    mits
    -0.69
    ccess
    -0.68
     Incarnation
    -0.67
    FORE
    -0.67
     Warehouse
    -0.67
    YL
    -0.66
     desperately
    -0.65
    POSITIVE LOGITS
    ened
    1.27
    ening
    1.18
    ener
    1.01
    edo
    0.88
    est
    0.88
     arrow
    0.86
    ness
    0.86
     sharp
    0.84
     strokes
    0.83
    erred
    0.80
    Activations Density 0.010%

    No Known Activations