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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 3-RES-JB
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    Explanations

    the name "Wolf" mentioned in a text

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "Wolf" in various contexts

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    bably
    -0.90
    acists
    -0.82
    pora
    -0.79
    acterial
    -0.78
    thritis
    -0.76
    ntil
    -0.76
    ursed
    -0.75
     millenn
    -0.72
     tradem
    -0.72
    nces
    -0.71
    POSITIVE LOGITS
    hound
    1.19
    enstein
    1.17
     Wolf
    1.15
    Wolf
    1.11
    sburg
    1.05
    pack
    1.04
    gang
    0.99
     Wolves
    0.99
    ram
    0.96
    bats
    0.96
    Activations Density 0.006%

    No Known Activations