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layer
int64
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neuron
int64
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mean_discovery
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[ " theoret", " Leban", " extraordin", "ель", "aturday" ]
[ "xym", "joint", "assisted", "iston", "atically" ]
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[ "тор", "MENTS", "Rich", "comple", "\u001e" ]
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[ "omyc", "organic", "illion", "ῶ", "thereum" ]
[ "eworthy", " circ", "bane", " bindings", "hers" ]
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[ " questionna", "vertis", "dorff", "obuf", "}{~" ]
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[ "ipsych", "idepress", "erp", "brainsci", " Boss" ]
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[ "grounds", "listed", "listing", "duc", " listing" ]
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[ "verages", " doxor", " cytotox", "း", " copolymers" ]
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[ " citiz", "cuador", "hip", "\r\n\r\n ", "hig" ]
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[ "past", "addam", " past", "Past", " Past" ]
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[ " artific", " refr", " nephe", " Indones", " Syscall" ]
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[ "strous", "ORAND", "cules", " questionna", "comings" ]
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[ " doxor", " behavi", "aryn", "ippi", "skirts" ]
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[ "task", "minist", " his", " Bar", "eered" ]
[ "urane", "pto", "othal", "opot", "ordial" ]
End of preview. Expand in Data Studio

Mamba-1.4B neuron atlas

Neuron-level statistics, automated labels and single-neuron steering generations for state-spaces/mamba-1.4b-hf. Produced by https://github.com/BurnyCoder/mamba-neuron-mechanistic-interpretability (methods, pre-registration and paper there).

A neuron (layer l, index i) is coordinate i of the gated SSM output a = y * SiLU(z), i.e. the input of mixer.out_proj (48 layers x 4096 = 196,608 neurons).

file rows content
neuron_stats.parquet 196,608 mean / std / skew / kurtosis / max / min / frac_pos on the discovery (2.32M tokens) and held-out (0.65M tokens) splits of NeelNanda/pile-10k; vocab kurtosis and top-5 promoted / suppressed tokens of W_U(g * w_i)
poles.parquet labelled poles local-LLM (qwen3.5:9b) label, held-out detection balanced accuracy, promoted tokens, highlighted top-firing snippets (JSON)
steering.parquet generations clamp-sweep screen and pre-registered confirmation generations with AxBench-style judge scores

Text snippets are short excerpts of the Pile (Gao et al. 2020) and keep the licences of their original sources; labels and judge scores are produced by a local LLM and are noisy (judge-vs-manual Cohen's kappa 0.55 on detection).

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