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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. 9036
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    Explanations

    phrases with the pattern "... in-depth ..."

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating depth or thoroughness in discussion

    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
    illac
    -0.67
     Independent
    -0.64
     Blues
    -0.64
     Doodle
    -0.64
     Reloaded
    -0.64
    Ń·
    -0.60
     Bullets
    -0.60
     Sorce
    -0.60
     Illum
    -0.60
     Intermediate
    -0.59
    POSITIVE LOGITS
    depth
    1.33
    line
    1.13
    built
    1.10
    demand
    1.10
    house
    1.03
    between
    1.03
    browser
    1.02
    sync
    1.02
    laws
    1.01
    flight
    1.01
    Activations Density 0.023%

    No Known Activations