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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. 4-RES-JB
    11. 2260
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    Explanations

    words related to difficult or unpleasant situations

    oai_token-act-pair · gpt-3.5-turbo

    intense expressions of frustration or difficulty

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

    No Comments

    Negative Logits
    States
    -0.69
    Random
    -0.68
    Broad
    -0.67
     Surveillance
    -0.67
    Recomm
    -0.66
    APD
    -0.65
    Ô
    -0.65
    PsyNetMessage
    -0.65
    Short
    -0.65
    Decre
    -0.64
    POSITIVE LOGITS
    enic
    1.04
    ishly
    1.00
    hound
    1.00
    hole
    0.98
    oise
    0.95
    holes
    0.88
    hur
    0.87
    bender
    0.85
    urous
    0.84
    fire
    0.82
    Activations Density 0.010%

    No Known Activations