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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. 23977
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    Explanations

    words related to animals, specifically focusing on species such as bison, rhino, and cougar

    oai_token-act-pair · gpt-3.5-turbo

    specific wildlife species and animal-related terms

    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
    blance
    -0.79
    Hardware
    -0.72
    Offline
    -0.70
    isSpecialOrderable
    -0.70
    æ©
    -0.69
    ļ
    -0.67
    ãĤ±
    -0.67
    stanbul
    -0.67
    §
    -0.67
    ASED
    -0.66
    POSITIVE LOGITS
     carc
    1.22
     herds
    1.20
     nests
    1.18
     species
    1.15
     larvae
    1.13
     herd
    1.11
     beetle
    1.09
     mating
    1.08
     habitat
    1.08
     breeding
    1.05
    Activations Density 0.209%

    No Known Activations