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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. 13034
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    Explanations

    mentions of training camps and related activities

    oai_token-act-pair · gpt-3.5-turbo

    mentions of training camps

    oai_token-act-pair · gpt-4o-miniTriggered 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
    Not in Any Lists

    No Comments

    Negative Logits
    ĸļ
    -0.78
    ctive
    -0.66
     regress
    -0.65
     platinum
    -0.64
    iasis
    -0.63
    wb
    -0.63
    hm
    -0.60
     antioxid
    -0.60
     pudding
    -0.60
     proble
    -0.58
    POSITIVE LOGITS
    fires
    1.07
    ground
    0.98
    camp
    0.98
     camp
    0.97
    agna
    0.94
    grounds
    0.93
    fire
    0.89
    bell
    0.87
    anas
    0.82
    aign
    0.80
    Activations Density 0.010%

    No Known Activations