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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. 3-RES-JB
    11. 17105
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    Explanations

    words related to outdoor environments or activities

    oai_token-act-pair · gpt-3.5-turbo

    references to outdoor settings or activities

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    ching
    -0.85
    bourg
    -0.79
    erion
    -0.78
    ochet
    -0.77
    orne
    -0.76
    geries
    -0.74
    phasis
    -0.73
    ogun
    -0.73
    orah
    -0.73
    aws
    -0.72
    POSITIVE LOGITS
     outdoor
    0.85
     seating
    0.82
     patio
    0.82
     recreation
    0.79
    etheless
    0.79
     enclosure
    0.76
     amph
    0.73
     minded
    0.70
     apparel
    0.70
     decoration
    0.68
    Activations Density 0.012%

    No Known Activations