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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. 9-RES-JB
    11. 22683
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    Explanations

    expressions related to desires or preferences

    oai_token-act-pair · gpt-3.5-turbo

    expressions of desire or demand from individuals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    adem
    -0.81
    çĶ°
    -0.70
    ourage
    -0.69
    Aim
    -0.69
    ema
    -0.67
    rentices
    -0.67
    Cooldown
    -0.67
     teasp
    -0.64
    iversal
    -0.64
    yan
    -0.62
    POSITIVE LOGITS
     their
    0.82
     themselves
    0.80
     refunds
    0.75
     THEIR
    0.68
     TVs
    0.67
     whichever
    0.65
     surprises
    0.63
     Beware
    0.63
    their
    0.62
     knowing
    0.62
    Activations Density 0.671%

    No Known Activations