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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. 0-RES-JB
    11. 7985
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    Explanations

    words related to types of grains, particularly focusing on corn

    oai_token-act-pair · gpt-3.5-turbo

    references to corn and its various uses

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     MP
    -0.70
    ibr
    -0.70
     Pu
    -0.69
     Sob
    -0.69
     Signed
    -0.69
    iveness
    -0.68
     Stur
    -0.68
     MB
    -0.68
     Rout
    -0.68
    member
    -0.68
    POSITIVE LOGITS
     corn
    3.54
    Corn
    2.17
     maize
    2.15
     Corn
    2.15
    corn
    2.03
     wheat
    1.74
     rye
    1.57
     grain
    1.57
     barley
    1.52
     cotton
    1.50
    Activations Density 0.018%

    No Known Activations