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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. 7-RES-JB
    11. 2699
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    Explanations

    words related to scientific processes and concepts, such as absorption, diffusion, regulation, and polarization

    oai_token-act-pair · gpt-3.5-turbo

    terms related to absorption and related physical processes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    soDeliveryDate
    -0.83
    awan
    -0.77
    HQ
    -0.75
    uterte
    -0.74
    iverse
    -0.73
    bold
    -0.73
    gets
    -0.70
     lawy
    -0.70
    epad
    -0.70
    Cola
    -0.66
    POSITIVE LOGITS
     coefficient
    1.10
     rate
    1.06
     Rate
    0.98
     mechanism
    0.96
     rates
    0.94
     coefficients
    0.88
     velocity
    0.88
     sickness
    0.88
     bias
    0.87
     factor
    0.85
    Activations Density 0.260%

    No Known Activations