Pietro Lesci PRO
pietrolesci
AI & ML interests
I like developing and applying causal methods to study the effect of training choices on models’ behaviour, including memorisation, shortcut learning, and tokenisation.
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InfoTokenizers/finewebedu-20B
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pietrolesci/pile-deduped
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a dataset
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pietrolesci/pythia-deduped-memorisation-profiles
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pietrolesci/me100M_finewebedu-20B_bpe32000minipile
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pietrolesci/me100M-tied_finewebedu-20B_bpe32000minipile
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pietrolesci/me850M_minipile_bpe32000minipile
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pietrolesci/me340M-tied_minipile_bpe32000minipile
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pietrolesci/me57M-tied_minipile_bpe2wp32000minipile
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pietrolesci/me57M-tied_minipile_bpe128000minipile
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pietrolesci/me57M-tied_minipile_wordpiece32000minipile
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pietrolesci/me57M-tied_minipile_bpe8064minipile
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pietrolesci/me57M-tied_minipile_bpe32000minipile
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pietrolesci/tokenisers
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datasets
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pietrolesci/pile-deduped
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pietrolesci/pythia-deduped-memorisation-profiles
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pietrolesci/pile-validation
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pietrolesci/pile-deduped-subset
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pietrolesci/pythia-deduped-stats
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pietrolesci/pythia-deduped-stats-raw
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pietrolesci/agnews
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pietrolesci/amazoncat-13k
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pietrolesci/wikitoxic
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pietrolesci/multiwoz_all_versions
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