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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. 2-RES-JB
    6. 50
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    Explanations

    references to the term "Wolf" at different levels of specificity, possibly related to a specific topic or entity named "Wolf"

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "Wolf" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    the word "Wolf" regardless of context

    oai_token-act-pair · gpt-4-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    bably
    -0.91
    pora
    -0.81
    acterial
    -0.80
    ntil
    -0.77
    acists
    -0.77
    thritis
    -0.73
    ursed
    -0.73
     tradem
    -0.73
    senal
    -0.72
    llular
    -0.72
    POSITIVE LOGITS
     Wolf
    1.29
    enstein
    1.26
    hound
    1.13
    Wolf
    1.13
    sburg
    1.06
     Wolves
    1.03
    pack
    0.98
    owitz
    0.98
     Fenrir
    0.95
    bats
    0.94
    Activations Density 0.007%

    No Known Activations