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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. 9-RES-JB
    11. 13235
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    Explanations

    words related to technology and infrastructure, specifically focusing on technological equipment and installations

    oai_token-act-pair · gpt-3.5-turbo

    variations of the word "work" and related actions or situations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ĸļ
    -0.90
     Bron
    -0.76
     Scand
    -0.73
     Trin
    -0.71
    £ı
    -0.69
     Rabbit
    -0.69
     Lemon
    -0.67
     Dahl
    -0.66
    ashtra
    -0.66
     Vi
    -0.65
    POSITIVE LOGITS
    ettings
    1.08
    acters
    1.02
    anship
    0.96
    ework
    0.93
    alog
    0.90
    ards
    0.89
    ences
    0.88
    aunts
    0.88
    ipment
    0.88
    istance
    0.87
    Activations Density 0.142%

    No Known Activations