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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. 7301
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    INDEX
    Explanations

    mentions of or related to sports players and their activities

    oai_token-act-pair · gpt-3.5-turbo

    references to players in a sports context

    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
    Operation
    -0.84
    ories
    -0.82
    ½
    -0.73
    ĺħ
    -0.72
    ħĭ
    -0.70
     Ples
    -0.69
     Cooking
    -0.66
    orship
    -0.65
    ²¾
    -0.63
    icity
    -0.62
    POSITIVE LOGITS
     drafted
    0.90
     kneeling
    0.82
     jerseys
    0.79
    inic
    0.78
     endors
    0.75
    amac
    0.73
     rosters
    0.73
     scouts
    0.72
    atu
    0.71
    Coach
    0.71
    Activations Density 0.098%

    No Known Activations