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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. 9-RES-JB
    11. 2924
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    Explanations

    phrases related to winning or losing streaks

    oai_token-act-pair · gpt-3.5-turbo

    references to consecutive wins or losses in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     GOODMAN
    -0.76
    Sov
    -0.67
    acus
    -0.63
    anooga
    -0.62
    Reviewed
    -0.62
    District
    -0.62
    Scale
    -0.61
     Orchestra
    -0.61
    ocate
    -0.60
    hammad
    -0.60
    POSITIVE LOGITS
     streak
    1.17
     lasting
    0.99
     streaks
    0.89
     spanning
    0.88
     Ended
    0.83
    uous
    0.81
    icity
    0.81
    lasting
    0.79
     longest
    0.77
     ending
    0.76
    Activations Density 0.078%

    No Known Activations