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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. 4-RES-JB
    11. 6341
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    Explanations

    information related to shooting or making shots in a sports context

    oai_token-act-pair · gpt-3.5-turbo

    terms related to basketball shots and shooting statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    ç«
    -0.75
    eday
    -0.72
    éĸ
    -0.70
    aml
    -0.70
    BD
    -0.70
     Bleach
    -0.69
    atom
    -0.68
    ombat
    -0.68
    edition
    -0.65
    DOS
    -0.65
    POSITIVE LOGITS
    ista
    0.84
    calling
    0.84
     passer
    0.83
     coach
    0.78
     gallery
    0.76
     coached
    0.75
     scorer
    0.73
    finder
    0.72
     alley
    0.72
     teammate
    0.71
    Activations Density 0.033%

    No Known Activations