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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. 1-RES-JB
    11. 6648
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    Explanations

    phrases or words related to participants or people attending events

    oai_token-act-pair · gpt-3.5-turbo

    mentions of participants or attendees at events

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     circumstance
    -0.65
    frog
    -0.63
    redo
    -0.61
     revenge
    -0.60
     mountainous
    -0.59
    smart
    -0.59
    bole
    -0.58
    interest
    -0.58
     reconciliation
    -0.57
    repair
    -0.57
    POSITIVE LOGITS
     attendees
    1.33
     Attend
    1.01
    goers
    1.00
    anooga
    0.89
     guests
    0.87
     attendance
    0.87
     delegates
    0.86
     attend
    0.84
    eers
    0.82
    paces
    0.79
    Activations Density 0.007%

    No Known Activations