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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. 9-RES-JB
    11. 5815
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    Explanations

    references to the rear of objects or vehicles

    oai_token-act-pair · gpt-3.5-turbo

    terms related to the rear part of vehicles

    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
    eteria
    -0.86
    âĸĪâĸĪ
    -0.85
    ensable
    -0.82
    wana
    -0.81
    etus
    -0.78
    etti
    -0.76
    ERE
    -0.75
    achu
    -0.74
    oleon
    -0.73
    âĸĪâĸĪâĸĪâĸĪ
    -0.72
    POSITIVE LOGITS
    ward
    1.31
    wards
    1.07
     axle
    0.97
    most
    0.95
     tyre
    0.94
    side
    0.94
    view
    0.92
    facing
    0.88
     lobe
    0.86
     derail
    0.84
    Activations Density 0.035%

    No Known Activations