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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 3-RES-JB
    6. 7395
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    INDEX
    Explanations

    lawyers or legal professionals mentioned in a text

    oai_token-act-pair · gpt-3.5-turbo

    references to legal professionals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    plings
    -0.93
    oppers
    -0.80
    urat
    -0.76
    auri
    -0.72
    ween
    -0.72
    wn
    -0.71
    pora
    -0.71
    bows
    -0.70
    inki
    -0.69
    aukee
    -0.67
    POSITIVE LOGITS
    itatively
    0.85
     examiner
    0.84
    hood
    0.82
    suit
    0.78
     Sergei
    0.75
     lawyer
    0.74
    yer
    0.74
    ate
    0.73
     solicitor
    0.72
    ess
    0.71
    Activations Density 0.026%

    No Known Activations