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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. 0-RES-JB
    11. 7693
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    Explanations

    food-related words

    oai_token-act-pair · gpt-3.5-turbo

    terms related to eating and food consumption

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     RTX
    -0.91
     royalties
    -0.73
     Errors
    -0.72
     Holding
    -0.67
     Papers
    -0.67
     Jonas
    -0.65
     Letters
    -0.64
     Pa
    -0.63
    href
    -0.63
     Practices
    -0.63
    POSITIVE LOGITS
     eater
    3.76
     Eater
    2.51
     Cater
    1.43
     beast
    1.42
     baker
    1.39
     taco
    1.32
     cater
    1.24
    eating
    1.15
     fisher
    1.15
     sleeper
    1.14
    Activations Density 0.051%

    No Known Activations