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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. 7-RES-JB
    11. 17103
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    Explanations

    participants in studies or experiments

    oai_token-act-pair · gpt-3.5-turbo

    references to study participants and their involvement

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    vell
    -0.67
     Bale
    -0.67
     actionGroup
    -0.67
     Shack
    -0.64
     Sense
    -0.62
     vengeance
    -0.61
    asso
    -0.59
    flu
    -0.59
    stones
    -0.58
    duc
    -0.58
    POSITIVE LOGITS
    cript
    0.87
     Participants
    0.80
     participant
    0.78
     enrolled
    0.74
    ividual
    0.71
    IAL
    0.71
     elig
    0.70
     participants
    0.70
    particip
    0.69
    hips
    0.68
    Activations Density 0.044%

    No Known Activations