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The recent Transformer-based pre-trained language models (e.g., BERT, Bi-directional Encoding Representations from Transformers 54 ) usually require a limited length of up to 512 sub-word tokens (where a word can be tokenised into several sub-words) as input due to the memory-demanding self-attention mechanism, while discharge summaries alone in MIMIC-III have on average around 1500 tokens or words 19 and up to over 10,000 tokens, not counting other types of clinical notes
Full catalog The Thin Safety Data and the Copper-Accumulation Question The most important thing to say about AHK-Cu's safety is also the least satisfying: there isn't much formal data
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Troubles digestifs : Certains utilisateurs rapportent des nauses ou des ballonnements, souvent lis la prise jeun

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