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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
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    Explanations

    mentions of various animals

    oai_token-act-pair · gpt-3.5-turbo

    mentions of specific animal species, particularly those that are dangerous or notable in discussions of wildlife management

    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
    inventoryQuantity
    -0.87
    Ô
    -0.82
    Offline
    -0.81
     Degree
    -0.79
     Transaction
    -0.76
    unda
    -0.76
     Revival
    -0.75
    issance
    -0.74
    Effective
    -0.73
    Registration
    -0.72
    POSITIVE LOGITS
     mammals
    1.60
     goats
    1.57
     reptiles
    1.55
     rabbits
    1.53
     rodents
    1.53
     primates
    1.51
     monkeys
    1.49
     apes
    1.48
     dolphins
    1.45
     elephants
    1.44
    Activations Density 0.257%

    No Known Activations