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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. 4-RES-JB
    11. 922
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    Explanations

    phrases related to tanks, such as "filling a tank with diesel" and "using a tank to knock down a wall."

    oai_token-act-pair · gpt-3.5-turbo

    references to tanks and their various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    âĸ¬
    -1.06
    ãĤ±
    -0.77
    女
    -0.75
     Lod
    -0.70
    PRES
    -0.68
    âĸ¬âĸ¬
    -0.67
    theless
    -0.67
    cause
    -0.67
    çīĪ
    -0.67
    éĹ
    -0.66
    POSITIVE LOGITS
    erness
    1.06
    tank
    0.92
    ard
    0.90
    arded
    0.88
    yard
    0.85
    roller
    0.85
    ards
    0.84
    ategory
    0.83
    rait
    0.80
     tank
    0.78
    Activations Density 0.012%

    No Known Activations