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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. 7-RES-JB
    11. 3921
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    Explanations

    phrases related to accumulation or a large quantity of items

    oai_token-act-pair · gpt-3.5-turbo

    references to "piles" or "piling" of various objects or situations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     warr
    -0.72
     livest
    -0.69
     obser
    -0.69
    javascript
    -0.67
    oral
    -0.66
    6666
    -0.65
    saf
    -0.62
    cers
    -0.62
    abad
    -0.62
    encers
    -0.61
    POSITIVE LOGITS
     piles
    1.06
     piling
    1.03
     pile
    0.97
     piled
    0.90
    bags
    0.78
    endium
    0.75
    aging
    0.74
     heap
    0.73
     loads
    0.73
    ump
    0.72
    Activations Density 0.030%

    No Known Activations