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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. 22645
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    Explanations

    phrases related to learning from mistakes and taking responsibility

    oai_token-act-pair · gpt-3.5-turbo

    references to learning from past mistakes

    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
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    No Comments

    Negative Logits
    atri
    -0.85
    andise
    -0.80
    osponsors
    -0.78
    translation
    -0.78
    \">
    -0.78
     GOODMAN
    -0.78
    Lago
    -0.76
     mosqu
    -0.76
    cise
    -0.75
    soDeliveryDate
    -0.75
    POSITIVE LOGITS
     mistakes
    1.70
     failings
    1.46
     failures
    1.45
     faults
    1.42
     errors
    1.32
     mistake
    1.26
     negligence
    1.26
     flaws
    1.25
     shortcomings
    1.25
     hindsight
    1.23
    Activations Density 0.922%

    No Known Activations