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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. 24141
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    INDEX
    Explanations

    the word "what" closely followed by a verb or subject/predicate structure

    oai_token-act-pair · gpt-3.5-turbo

    phrases that highlight the concept of "what" and its significance in various contexts

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    robe
    -0.71
    ardless
    -0.70
    ãģ®éŃĶ
    -0.67
    astical
    -0.65
    ubs
    -0.65
    UNE
    -0.65
    imen
    -0.64
    say
    -0.64
    lich
    -0.63
    trop
    -0.62
    POSITIVE LOGITS
     happens
    1.33
     happened
    1.32
     separates
    1.22
     distinguishes
    1.10
     transpired
    1.04
     bothers
    1.03
     mattered
    1.00
     motiv
    0.98
    soever
    0.95
     attracts
    0.93
    Activations Density 0.044%

    No Known Activations