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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 9-RES-JB
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    Explanations

    references to carnivals and related activities

    oai_token-act-pair · gpt-3.5-turbo

    terms related to carnivals and food, particularly in the context of enjoyment and indulgence

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    arta
    -0.74
    Maker
    -0.74
    NESS
    -0.73
     Âł Âł Âł Âł
    -0.67
    ORN
    -0.67
    ANY
    -0.64
     Resolution
    -0.64
     Angle
    -0.63
    使
    -0.62
     transcript
    -0.61
    POSITIVE LOGITS
    ivals
    1.07
    iously
    1.03
    atory
    1.00
    ival
    0.97
    acebook
    0.91
    ulatory
    0.90
    itas
    0.89
    pillar
    0.87
    uitous
    0.86
    ulum
    0.84
    Activations Density 0.086%

    No Known Activations