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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. 23440
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    Explanations

    action verbs related to winning and success

    oai_token-act-pair · gpt-3.5-turbo

    indicators of victory or winning situations

    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
     doesnt
    -0.68
     pics
    -0.66
     didnt
    -0.65
     whats
    -0.62
     americ
    -0.61
     alot
    -0.61
     somet
    -0.61
     info
    -0.60
     "@
    -0.58
     VIDEOS
    -0.57
    POSITIVE LOGITS
     ÂŃ
    0.77
     fundamentally
    0.75
    ,[
    0.74
     therefore
    0.74
     precisely
    0.74
     consequently
    0.70
     profoundly
    0.70
    iless
    0.69
    )—
    0.68
    ïve
    0.68
    Activations Density 1.495%

    No Known Activations