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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. 6-RES-JB
    11. 20512
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    Explanations

    phrases related to abundance or high quantity

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to significance or magnitude

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     horizont
    -0.76
    anwhile
    -0.66
     Creator
    -0.65
    IDS
    -0.65
    ioxide
    -0.64
     makers
    -0.62
    ysc
    -0.60
     Beaut
    -0.60
     reigning
    -0.60
    aten
    -0.59
    POSITIVE LOGITS
     impression
    0.95
    sense
    0.86
     mistake
    0.76
     contribution
    0.76
     allowance
    0.74
     dent
    0.71
     disappear
    0.71
     noises
    0.70
     fuss
    0.70
     strides
    0.70
    Activations Density 0.135%

    No Known Activations