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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. 1463
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    Explanations

    numerical values expressed as ranges, with a focus on margins of error

    oai_token-act-pair · gpt-3.5-turbo

    numerical indicators of changes or fluctuations, particularly concerning declines and margins of error

    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
    soDeliveryDate
    -0.98
    NetMessage
    -0.93
    rahim
    -0.88
    hots
    -0.84
    ively
    -0.82
    oros
    -0.80
    20439
    -0.79
    SourceFile
    -0.78
    ible
    -0.76
    istry
    -0.74
    POSITIVE LOGITS
    thur
    0.85
     Noon
    0.68
    terness
    0.67
     (-
    0.65
     Fidel
    0.65
     Nom
    0.65
     noon
    0.63
     Vie
    0.62
     Sax
    0.62
    cise
    0.61
    Activations Density 0.039%

    No Known Activations