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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 23998
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    INDEX
    Explanations

    mentions of the word "Tiger" with varying levels of specificity, including specific people, locations, and species

    oai_token-act-pair · gpt-3.5-turbo

    references to the term "Tiger" and its various contexts, particularly in relation to sports and animals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inventoryQuantity
    -0.78
    ĵĺ
    -0.77
    к
    -0.74
    ACP
    -0.72
    earchers
    -0.71
    FontSize
    -0.71
    Philadelphia
    -0.71
    mble
    -0.70
    EngineDebug
    -0.70
    atform
    -0.70
    POSITIVE LOGITS
     Tiger
    1.00
     Woods
    0.91
     Tigers
    0.88
     tiger
    0.78
     tigers
    0.78
    iful
    0.77
    culosis
    0.76
    opard
    0.75
    emonium
    0.74
     stripes
    0.70
    Activations Density 0.018%

    No Known Activations