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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. 6-RES-JB
    11. 12845
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    Explanations

    statistics related to basketball players, focusing on rebounds specifically

    oai_token-act-pair · gpt-3.5-turbo

    statistics related to basketball rebounds

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    âĸ¬âĸ¬
    -0.77
    iHUD
    -0.74
    OPA
    -0.71
    anto
    -0.66
     Pebble
    -0.65
    cas
    -0.65
    «ĺ
    -0.63
    gra
    -0.63
     Masonic
    -0.62
     Mustang
    -0.61
    POSITIVE LOGITS
    ilion
    0.80
    hots
    0.78
    halla
    0.75
    acks
    0.75
    uler
    0.75
     rebounds
    0.73
    aceous
    0.73
    atoon
    0.73
    iers
    0.70
    olars
    0.70
    Activations Density 0.035%

    No Known Activations