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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 drivers in various situations, such as driving incidents and interactions with law enforcement

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the word "driver" and its variants

    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
    achu
    -0.76
     Seym
    -0.75
    ropolitan
    -0.75
    ertain
    -0.74
    yss
    -0.73
    iversal
    -0.73
     Flavoring
    -0.73
    sembly
    -0.71
    ansion
    -0.71
    aeper
    -0.71
    POSITIVE LOGITS
     driver
    0.96
     drivers
    0.91
     pige
    0.88
    less
    0.85
    driver
    0.84
    esses
    0.81
     bees
    0.80
    ways
    0.79
    lane
    0.78
    driving
    0.76
    Activations Density 0.016%

    No Known Activations