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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. 3-RES-JB
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    Explanations

    references to sports teams named "Tigers"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the "Tigers" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    uters
    -0.79
    ITED
    -0.76
    iture
    -0.74
    Ïĥ
    -0.72
    trak
    -0.72
    quickShipAvailable
    -0.71
     srfAttach
    -0.71
    ATTLE
    -0.69
    UTERS
    -0.69
    roximately
    -0.68
    POSITIVE LOGITS
     Tigers
    1.29
    emonium
    0.91
     Tiger
    0.85
     Pistons
    0.81
     tigers
    0.79
     Unleashed
    0.78
    igers
    0.78
     Sting
    0.75
    opard
    0.74
    poons
    0.74
    Activations Density 0.009%

    No Known Activations