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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. 3-RES-JB
    11. 9087
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    Explanations

    phrases related to growing or nurturing something, such as plants or communities

    oai_token-act-pair · gpt-3.5-turbo

    terms related to the act of cultivating or the concept of cultivation

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    POS
    -0.74
    reme
    -0.70
    que
    -0.67
     attacker
    -0.65
    inventoryQuantity
    -0.64
    asking
    -0.64
    andro
    -0.63
     coron
    -0.62
    PLE
    -0.61
    por
    -0.60
    POSITIVE LOGITS
     cultivate
    0.93
     cultivated
    0.88
     gardens
    0.85
     cultivating
    0.84
    ivating
    0.81
     cultivation
    0.80
     Farming
    0.80
    flower
    0.79
     cultiv
    0.78
    folios
    0.78
    Activations Density 0.017%

    No Known Activations