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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. 0-RES-JB
    11. 11580
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    Explanations

    mentions of specific terms, like "bill" or "hound," with varying levels of activation

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "bill" and "hound," indicating a focus on specific legislation or discussions related to dogs

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Trails
    -0.63
     Oro
    -0.62
     Jung
    -0.61
     grips
    -0.58
     cardio
    -0.57
     Trends
    -0.57
     mig
    -0.56
     Tra
    -0.56
     Cout
    -0.55
     refres
    -0.55
    POSITIVE LOGITS
    bill
    4.57
    hound
    1.41
    peak
    1.32
    bil
    1.31
    BILL
    1.24
    tons
    1.15
    quit
    1.03
    seeing
    1.00
    fare
    0.97
    pots
    0.95
    Activations Density 0.033%

    No Known Activations