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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. 24488
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    Explanations

    phrases related to decision-making or evaluation of situations

    oai_token-act-pair · gpt-3.5-turbo

    contexts related to effectiveness and efficiency

    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
     Flavoring
    -0.68
     Franch
    -0.57
     dumps
    -0.55
     cabinets
    -0.55
     Awakens
    -0.53
     Fighting
    -0.53
     AMA
    -0.52
    thia
    -0.52
     houses
    -0.52
     STL
    -0.52
    POSITIVE LOGITS
     fraught
    0.66
    SourceFile
    0.63
    ŃĶ
    0.60
     inex
    0.58
     waning
    0.58
    IER
    0.58
    avering
    0.58
    ------------------------------------------------
    0.56
    factor
    0.56
    PLIC
    0.56
    Activations Density 0.989%

    No Known Activations