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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. 8-RES-JB
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    Explanations

    instances where a specific word or concept is mentioned in a text

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "mention" and its variations

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    ¯¯¯¯¯¯¯¯
    -0.81
    sis
    -0.80
    quer
    -0.79
    ¯¯
    -0.74
    zers
    -0.71
    agos
    -0.70
    ¯¯¯¯
    -0.69
    ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
    -0.67
    sett
    -0.67
    onew
    -0.66
    POSITIVE LOGITS
     mentioning
    0.95
    lihood
    0.89
     mentions
    0.86
     aloud
    0.78
     Kislyak
    0.77
     mention
    0.73
     prominently
    0.73
     names
    0.68
     Neph
    0.66
    lessly
    0.65
    Activations Density 0.050%

    No Known Activations