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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 16688
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    Explanations

    phrases related to activities or events that are not easily visible or known to the public, typically happening backstage or off-camera

    oai_token-act-pair · gpt-3.5-turbo

    references to "behind the scenes" activities or contexts

    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
    Not in Any Lists

    No Comments

    Negative Logits
    heit
    -0.82
    rill
    -0.78
    mington
    -0.78
    arcity
    -0.78
    urdue
    -0.74
    haps
    -0.72
    gling
    -0.71
    apa
    -0.71
    liam
    -0.70
    rab
    -0.69
    POSITIVE LOGITS
     filming
    0.74
    spection
    0.71
     reconnaissance
    0.71
     performer
    0.69
     workings
    0.67
     scenes
    0.67
     talents
    0.66
     coaching
    0.66
     machinery
    0.65
     camera
    0.64
    Activations Density 0.038%

    No Known Activations