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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 7-RES-JB
    6. 15817
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    Explanations

    phrases related to specific topics or fields, such as "area of expertise" or "area of concern"

    oai_token-act-pair · gpt-3.5-turbo

    phrases that denote specific domains or categories of expertise

    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
     guiActive
    -0.93
     Picks
    -0.76
    aciously
    -0.66
    wt
    -0.65
    pps
    -0.64
    wives
    -0.63
    advertisement
    -0.63
    soDeliveryDate
    -0.63
    frog
    -0.63
    uristic
    -0.62
    POSITIVE LOGITS
     expertise
    0.85
     specialization
    0.83
     specificity
    0.80
     overlap
    0.80
     contention
    0.78
     interest
    0.76
     weakness
    0.76
     accommodation
    0.74
     refinement
    0.74
     deprivation
    0.73
    Activations Density 0.080%

    No Known Activations