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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. 18040
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    Explanations

    percentage values

    oai_token-act-pair · gpt-3.5-turbo

    numerical percentages and their significance in various 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
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    No Comments

    Negative Logits
    ande
    -0.64
     rematch
    -0.59
    quickShipAvailable
    -0.57
     comrades
    -0.57
    iphany
    -0.57
    aunts
    -0.56
     fatig
    -0.55
     pian
    -0.55
     beaut
    -0.55
     overcame
    -0.54
    POSITIVE LOGITS
    %%
    0.86
    illac
    0.82
    %);
    0.82
    %
    0.78
     brunt
    0.78
     percent
    0.77
    %]
    0.74
    thirds
    0.74
    gross
    0.72
     fraction
    0.71
    Activations Density 0.149%

    No Known Activations