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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. 1-RES-JB
    11. 12897
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    Explanations

    adjectives related to rough or challenging terrain

    oai_token-act-pair · gpt-3.5-turbo

    descriptive terms related to difficult or challenging conditions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    abetic
    -1.03
    reme
    -0.96
    ership
    -0.91
    ulhu
    -0.86
    aminer
    -0.85
    umers
    -0.85
    ©¶æ
    -0.84
    aret
    -0.83
    anguage
    -0.82
    ande
    -0.82
    POSITIVE LOGITS
     rocky
    1.29
     volcanic
    0.99
     shores
    0.93
     env
    0.82
     paths
    0.81
     seas
    0.79
     tumultuous
    0.79
     uneven
    0.78
     waters
    0.77
     turbulent
    0.76
    Activations Density 0.030%

    No Known Activations