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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. 6-RES-JB
    11. 964
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    INDEX
    Explanations

    data formatted as bullet points

    oai_token-act-pair · gpt-3.5-turbo

    numerical information or specific measures related to processes or procedures

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Wander
    -0.78
     Thornton
    -0.71
    ardless
    -0.69
    atis
    -0.66
     midway
    -0.66
    yan
    -0.66
     neighb
    -0.65
    sburgh
    -0.65
    cules
    -0.65
    ury
    -0.64
    POSITIVE LOGITS
    âĹı
    1.10
    âĸł
    0.97
    âľ
    0.85
    ·
    0.84
    âĺħ
    0.84
    âĢ¢
    0.82
    ðĿ
    0.80
    ³³³
    0.80
    ³³³³³³³³
    0.78
    ³³³³
    0.76
    Activations Density 0.090%

    No Known Activations