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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. 11-RES-JB
    11. 16587
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    INDEX
    Explanations

    phrases emphasizing a high quantity or intensity of something

    oai_token-act-pair · gpt-3.5-turbo

    quantities or levels of abundance

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ĪĴ
    -0.88
    agonists
    -0.87
    atures
    -0.84
    ħĭ
    -0.84
    ATURES
    -0.83
    selves
    -0.81
    endants
    -0.81
    ems
    -0.80
    ades
    -0.80
    onyms
    -0.80
    POSITIVE LOGITS
     negativity
    0.96
     firepower
    0.93
     hassle
    0.91
     crap
    0.91
     baggage
    0.89
     attention
    0.88
     fun
    0.88
     detail
    0.87
     trouble
    0.86
     else
    0.86
    Activations Density 0.065%

    No Known Activations