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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. 11-RES-JB
    11. 1382
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    Explanations

    words related to actions or events that cause a negative outcome or impact

    oai_token-act-pair · gpt-3.5-turbo

    phrases and structures indicating causation

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     supervised
    -0.86
    emouth
    -0.83
     vetted
    -0.71
    fitting
    -0.70
     helped
    -0.68
     protecting
    -0.68
    lished
    -0.68
    good
    -0.68
     translated
    -0.67
     compliments
    -0.67
    POSITIVE LOGITS
     lose
    1.56
     succumb
    1.44
     fail
    1.42
     stumble
    1.39
     suffer
    1.36
     perish
    1.31
     relapse
    1.31
     lapse
    1.30
     explode
    1.29
     crumble
    1.28
    Activations Density 0.240%

    No Known Activations