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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. 0-RES-JB
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    Explanations

    mentions of "wheels."

    oai_token-act-pair · gpt-3.5-turbo

    references to wheeled vehicles and components

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Sof
    -0.66
     Foster
    -0.65
    ides
    -0.64
     absorbed
    -0.64
     Feder
    -0.62
     concentration
    -0.62
    iser
    -0.59
     suspect
    -0.59
     Fay
    -0.59
     acc
    -0.59
    POSITIVE LOGITS
    wheel
    4.50
    whe
    2.83
    Wheel
    2.45
     wheel
    1.93
     Wheel
    1.82
     Wheels
    1.62
     wheels
    1.55
    Whe
    1.30
    wagon
    1.17
    leaf
    1.03
    Activations Density 0.012%

    No Known Activations