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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. 24154
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    Explanations

    information about deadlines and expected dates

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating anticipation of future events or decisions

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
     transpl
    -0.74
    thood
    -0.72
    escent
    -0.71
    aeda
    -0.68
    obook
    -0.67
    ories
    -0.67
     pioneered
    -0.65
     Rebell
    -0.65
     revol
    -0.64
    seless
    -0.63
    POSITIVE LOGITS
    nesday
    1.07
     afternoon
    1.00
    noon
    0.95
     noon
    0.94
     deadline
    0.90
    uesday
    0.89
    morrow
    0.89
    Monday
    0.88
    Tuesday
    0.88
    morning
    0.87
    Activations Density 0.271%

    No Known Activations