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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. 7-RES-JB
    6. 5589
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    Explanations

    instructions or steps in a process

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to food preparation and cooking techniques

    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
    Not in Any Lists

    No Comments

    Negative Logits
     Urug
    -0.68
     Samp
    -0.67
     Blanc
    -0.65
     Moreno
    -0.58
     Mole
    -0.58
     sacrific
    -0.56
    obos
    -0.55
    idates
    -0.55
     Lump
    -0.54
     Matter
    -0.53
    POSITIVE LOGITS
    rina
    0.65
    iscons
    0.59
    animous
    0.59
    okemon
    0.58
    iphate
    0.58
    Army
    0.57
    uilding
    0.57
     Railroad
    0.56
     Bleach
    0.56
    ucky
    0.56
    Activations Density 0.559%

    No Known Activations