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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. 23404
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    INDEX
    Explanations

    phrases related to performance excellence or standout qualities

    oai_token-act-pair · gpt-3.5-turbo

    descriptors of performance and quality in sports contexts

    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
    Tube
    -0.77
    lene
    -0.71
    comfort
    -0.70
    skirts
    -0.70
     Canaver
    -0.70
    helle
    -0.69
     ®
    -0.68
    atel
    -0.67
    bara
    -0.67
    $$$$
    -0.65
    POSITIVE LOGITS
     positional
    1.20
     defensive
    1.18
     offense
    1.10
     goalt
    1.09
     quarterback
    1.05
     lineback
    1.05
     passer
    1.04
     offensive
    1.04
     matchup
    1.03
     defensively
    1.01
    Activations Density 0.153%

    No Known Activations