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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. 2682
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    Explanations

    instructions for baking and cooking

    oai_token-act-pair · gpt-3.5-turbo

    instructions related to food preparation and baking processes

    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
     Nanto
    -0.70
    utsche
    -0.66
    OTA
    -0.65
    href
    -0.65
     Jaguar
    -0.64
     Samar
    -0.64
    ocrin
    -0.63
     adrenaline
    -0.63
     Gund
    -0.63
    language
    -0.62
    POSITIVE LOGITS
     parchment
    1.07
     pastry
    0.97
     evenly
    0.97
     freezer
    0.96
     moist
    0.92
     tray
    0.91
     tablespoon
    0.89
     dough
    0.88
     thickness
    0.87
     mound
    0.86
    Activations Density 0.203%

    No Known Activations