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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. 11-RES-JB
    11. 11137
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    Explanations

    phrases related to scoring or attempting to score in sports, particularly football (soccer)

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to sports, specifically focusing on actions and locations in a game scenario

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ventions
    -0.76
    conom
    -0.71
    init
    -0.70
    OUP
    -0.69
    deals
    -0.69
    nces
    -0.63
    cases
    -0.60
    Craft
    -0.59
    isen
    -0.58
     Compare
    -0.58
    POSITIVE LOGITS
     underside
    0.95
     net
    0.91
     basket
    0.89
     goalkeeper
    0.89
     fence
    0.81
     rim
    0.81
     upright
    0.80
     keeper
    0.78
     corner
    0.78
     sideline
    0.76
    Activations Density 0.058%

    No Known Activations