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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 2062
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    Explanations

    terms related to American football positions, specifically focusing on tight ends and wide receivers

    oai_token-act-pair · gpt-3.5-turbo

    references to football positions, particularly tight ends and wide receivers

    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
    isf
    -0.80
     Ink
    -0.76
    itarian
    -0.71
    xit
    -0.71
     organisers
    -0.69
     Cald
    -0.68
    elvet
    -0.68
     plur
    -0.66
     Orwell
    -0.66
     Newsp
    -0.66
    POSITIVE LOGITS
     linebacker
    1.07
     rusher
    1.02
     linebackers
    1.01
     lineman
    0.95
     QB
    0.93
     linemen
    0.93
     cornerback
    0.91
     coach
    0.91
     quarterback
    0.90
     quarterbacks
    0.86
    Activations Density 0.157%

    No Known Activations