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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. 1-RES-JB
    11. 24248
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    Explanations

    references to subway stations

    oai_token-act-pair · gpt-3.5-turbo

    mentions of subway systems

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Ul
    -0.74
     Williamson
    -0.71
    IRD
    -0.69
    Copyright
    -0.67
    yer
    -0.65
    Remote
    -0.64
     Odin
    -0.64
    wine
    -0.63
     Bret
    -0.63
    ================================================================
    -0.63
    POSITIVE LOGITS
     subway
    1.25
     Subway
    1.01
    avorite
    1.00
    ngth
    1.00
    orough
    0.85
     entrances
    0.83
     commute
    0.81
     Railroad
    0.79
     station
    0.79
     fare
    0.78
    Activations Density 0.010%

    No Known Activations