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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 1-RES-JB
    6. 7802
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    Explanations

    the word "Most" followed by various contexts

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "most" in various contexts

    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
    rompt
    -0.74
     Travels
    -0.68
     DOT
    -0.67
    arium
    -0.67
     CARD
    -0.66
    thur
    -0.66
    pload
    -0.66
    pless
    -0.63
     LOT
    -0.60
    plan
    -0.59
    POSITIVE LOGITS
     importantly
    1.01
     Wanted
    0.95
     Helpful
    0.90
     Likely
    0.90
     Important
    0.88
     important
    0.82
    entimes
    0.81
    likely
    0.80
     notable
    0.80
    egu
    0.75
    Activations Density 0.048%

    No Known Activations