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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. 4-RES-JB
    11. 22462
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    Explanations

    words related to capturing information or data

    oai_token-act-pair · gpt-3.5-turbo

    terms related to the concept of capturing or recording

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

    No Comments

    Negative Logits
     amen
    -0.69
     notor
    -0.68
    bye
    -0.67
    pace
    -0.66
     inclined
    -0.64
     hesitate
    -0.63
     err
    -0.63
     occas
    -0.62
    jab
    -0.61
    wa
    -0.61
    POSITIVE LOGITS
    racuse
    0.86
    ively
    0.84
    nect
    0.79
    oufl
    0.71
    alogue
    0.70
     captured
    0.69
    doors
    0.68
    eers
    0.68
    aucuses
    0.68
    otes
    0.67
    Activations Density 0.015%

    No Known Activations