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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 21010
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    Explanations

    terms related to intense focus or concentration

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the substring "int" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    hyde
    -0.90
    wagen
    -0.78
    ĸļ
    -0.77
    Reviewer
    -0.76
    buster
    -0.73
    Train
    -0.69
    jriwal
    -0.68
    SEA
    -0.66
    SHIP
    -0.66
     ãĤµãĥ¼ãĥĨãĤ£ãĥ¯ãĥ³
    -0.66
    POSITIVE LOGITS
    ention
    1.09
    ellect
    1.06
    ensions
    1.00
    itial
    0.98
    ension
    0.94
    ended
    0.93
    ract
    0.92
    icult
    0.92
    ensive
    0.90
    ensity
    0.89
    Activations Density 0.014%

    No Known Activations