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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. 10-RES-JB
    11. 8457
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    Explanations

    words related to perception or attention, such as seeing, hearing, noticing, recognizing, and believing

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     teasp
    -0.86
    rontal
    -0.81
    =~=~
    -0.72
    ActionCode
    -0.69
    DeliveryDate
    -0.69
     subur
    -0.68
     earthqu
    -0.67
    è£ħ
    -0.67
     exting
    -0.66
    ãĥ¯ãĥ³
    -0.66
    POSITIVE LOGITS
     themselves
    0.97
     theirs
    0.96
     me
    0.92
     us
    0.88
     their
    0.83
     him
    0.75
     it
    0.75
     alike
    0.73
     THEIR
    0.72
     this
    0.71
    Activations Density 0.298%

    No Known Activations