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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. 6-RES-JB
    11. 20492
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    Explanations

    phrases related to modes of transportation

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to riding and motion

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    mberg
    -0.88
     ende
    -0.87
    zsche
    -0.82
    ternity
    -0.74
     specificity
    -0.74
    mble
    -0.73
    insk
    -0.73
     situ
    -0.72
    teness
    -0.72
    ertodd
    -0.71
    POSITIVE LOGITS
     bandwagon
    0.96
    wagon
    0.88
     wagon
    0.85
     horses
    0.84
     broom
    0.79
     roller
    0.78
    roller
    0.76
     Ride
    0.76
     carts
    0.75
     stairs
    0.73
    Activations Density 0.128%

    No Known Activations