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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 1867
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    Explanations

    words related to quantitative measurement or assessment

    oai_token-act-pair · gpt-3.5-turbo

    terms related to indicators or measurements of various conditions or qualities

    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
    Not in Any Lists

    No Comments

    Negative Logits
    ©¶æ
    -0.85
    ahime
    -0.82
    ategory
    -0.80
    frey
    -0.78
    artney
    -0.77
    ernel
    -0.76
    LOAD
    -0.74
    lishing
    -0.74
    ŃĶ
    -0.70
    uthor
    -0.70
    POSITIVE LOGITS
     indicators
    1.05
     markers
    0.96
     indicator
    0.86
     marker
    0.86
     gauge
    0.85
     correlate
    0.78
     gau
    0.73
    posts
    0.73
     variables
    0.72
    mentioned
    0.69
    Activations Density 0.051%

    No Known Activations