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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. 16822
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    Explanations

    quantitative terms related to measurement and comparison

    oai_token-act-pair · gpt-3.5-turbo

    terms related to quantifiable entities and structures in various contexts

    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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    Negative Logits
    Õ
    -0.80
    âĸ¬
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    Ô
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    ãĤ¨ãĥ«
    -0.73
    ãĥį
    -0.72
    Benz
    -0.71
    CHAR
    -0.70
    çĶ°
    -0.69
    ãĤ¿
    -0.69
    Tur
    -0.69
    POSITIVE LOGITS
    hips
    1.34
    poons
    1.20
    etting
    1.13
    ynthesis
    1.12
    hip
    1.10
    uggest
    1.10
    avers
    1.06
    heet
    1.05
    ourcing
    1.02
    ettings
    1.01
    Activations Density 0.415%

    No Known Activations