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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. 9685
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    Explanations

    mentions of specific names and titles, particularly "Wenger" and "Wally", as well as locations like "Worcester"

    oai_token-act-pair · gpt-3.5-turbo

    proper nouns, particularly names and places

    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
    oration
    -0.81
    omaly
    -0.76
    icted
    -0.76
    icts
    -0.74
    ibility
    -0.74
    pmwiki
    -0.70
     Defenders
    -0.69
    alion
    -0.69
    ividual
    -0.68
    itors
    -0.67
    POSITIVE LOGITS
     Wenger
    0.84
    sonian
    0.81
    pin
    0.80
    ukong
    0.78
    rior
    0.75
    pins
    0.74
     vi
    0.74
    risome
    0.72
    tons
    0.70
    esome
    0.70
    Activations Density 0.017%

    No Known Activations