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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. 1-RES-JB
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    Explanations

    instances of the word "Rangers"

    oai_token-act-pair · gpt-3.5-turbo

    the presence of the word "Rangers"

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ¢
    -0.83
    à
    -0.80
    ãĥ´ãĤ¡
    -0.76
    jamin
    -0.74
    elly
    -0.74
    cus
    -0.73
    ĵ
    -0.70
    ̶
    -0.69
    itia
    -0.68
    ãĥĭ
    -0.65
    POSITIVE LOGITS
     Rangers
    1.39
     Ranger
    0.97
    folk
    0.80
     Spirits
    0.78
     Regiment
    0.78
     ranger
    0.76
     Rays
    0.74
     outfielder
    0.74
     resil
    0.73
     Jagu
    0.72
    Activations Density 0.006%

    No Known Activations