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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. 17485
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    Explanations

    verbs related to achieving, acquiring, or obtaining something

    oai_token-act-pair · gpt-3.5-turbo

    phrases associated with acquiring or obtaining something

    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
    Downloadha
    -0.84
     pse
    -0.72
     Oops
    -0.69
    çīĪ
    -0.66
    raid
    -0.64
     Countdown
    -0.64
     Neurolog
    -0.64
    idia
    -0.63
    bryce
    -0.63
    heses
    -0.63
    POSITIVE LOGITS
     attention
    1.17
     traction
    1.12
     sympathy
    1.10
     momentum
    1.09
     funds
    0.98
     awareness
    0.98
     approval
    0.97
     signatures
    0.95
     goodwill
    0.95
     leverage
    0.92
    Activations Density 0.251%

    No Known Activations