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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. 14020
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    INDEX
    Explanations

    quantities of liquids or substances (e.g., gallons, barrels, tonnes) mentioned in the text

    oai_token-act-pair · gpt-3.5-turbo

    quantities and measurements related to resource production and consumption

    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
     Atari
    -0.74
    gotten
    -0.72
     Scand
    -0.71
     Assass
    -0.66
     precedence
    -0.66
     Chinatown
    -0.65
     Doodle
    -0.65
     pse
    -0.63
     Neo
    -0.63
     Norton
    -0.62
    POSITIVE LOGITS
     lbs
    0.98
    poons
    0.94
     pounds
    0.93
     worth
    0.89
     tonnes
    0.89
     annually
    0.87
     apiece
    0.86
     litres
    0.85
    abytes
    0.84
    awatts
    0.84
    Activations Density 0.091%

    No Known Activations