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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. 10-RES-JB
    11. 12558
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    Explanations

    phrases related to heating and cooling instructions for different processes or appliances

    oai_token-act-pair · gpt-3.5-turbo

    terms related to heating processes and temperature settings, specifically in the context of ovens

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    omics
    -0.73
    ibia
    -0.69
    escription
    -0.68
    utan
    -0.66
    SN
    -0.65
     Shape
    -0.64
    uties
    -0.64
    umper
    -0.63
    ograms
    -0.63
     pse
    -0.62
    POSITIVE LOGITS
     oven
    1.16
     lamps
    1.11
     vents
    1.07
     furnace
    1.04
     stove
    0.97
     radiator
    0.93
     heater
    0.93
     heating
    0.92
     grill
    0.91
     fireplace
    0.91
    Activations Density 0.183%

    No Known Activations