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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. 1-RES-JB
    6. 23492
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    INDEX
    Explanations

    words related to mythical or fictional creatures, particularly monsters

    oai_token-act-pair · gpt-3.5-turbo

    references to "monsters" in various contexts

    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
    arers
    -0.82
    ories
    -0.82
    atche
    -0.77
    omers
    -0.77
    blance
    -0.75
     cort
    -0.75
    lar
    -0.74
     lav
    -0.74
    lay
    -0.72
    nor
    -0.72
    POSITIVE LOGITS
     monster
    1.14
     monsters
    1.09
     beasts
    0.92
     Fenrir
    0.86
     beast
    0.85
     Monstrous
    0.80
     Beasts
    0.79
    monster
    0.78
     Monsters
    0.77
    Monster
    0.77
    Activations Density 0.014%

    No Known Activations