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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. 19618
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    Explanations

    terms related to receiving positive outcomes or advantages

    oai_token-act-pair · gpt-3.5-turbo

    terms related to benefiting or advantage

    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
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    No Comments

    Negative Logits
    rez
    -0.68
    body
    -0.64
     caul
    -0.63
    olver
    -0.60
     residues
    -0.59
    viks
    -0.58
     faults
    -0.58
    pas
    -0.57
    kill
    -0.57
     fault
    -0.56
    POSITIVE LOGITS
     enormously
    1.04
     immensely
    1.04
     financially
    1.03
     tremendously
    1.00
     greatly
    0.98
     tremend
    0.90
    igan
    0.87
     materially
    0.84
    ischer
    0.81
     hugely
    0.78
    Activations Density 0.062%

    No Known Activations