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PDF rendering of File:PRcoords_Cheatsheet.svg. Fonts work well in this copy, but all the equal signs in "=>" get copied to some not-a-character due to bad ligature handling. So if you are doing some copy-paste-to-console job, remember to fix all those places.
'''bold''' ''italics'' <sup>superscript</sup> <sub>superscript</sub> → bold: → italics: → superscript → subscript <s>strikeout</s> <u>underline</u> <big>big ...
Self-refine [38] prompts the LLM to solve the problem, then prompts the LLM to critique its solution, then prompts the LLM to solve the problem again in view of the problem, solution, and critique. This process is repeated until stopped, either by running out of tokens, time, or by the LLM outputting a "stop" token.
To see PDF and PNG files, please see Category:Wikimedia promotion. Work derivate and translated from Image:Cheatsheet-en.pdf or Image:Cheatsheet-en.png. Note. PNG files are just for preview, and should soon be deleted. PDF files were the former ones (what do we do with them now ?) SVG files are the new ones.
Retrieval Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
Wiki markup quick reference (PDF download) For a full list of editing commands, see Help:Wikitext; For including parser functions, variables and behavior switches, see Help:Magic words; For a guide to displaying mathematical equations and formulas, see Help:Displaying a formula; For a guide to editing, see Wikipedia:Contributing to Wikipedia
These printable keyboard shortcut symbols will make your life so much easier. The post 96 Shortcuts for Accents and Symbols: A Cheat Sheet appeared first on Reader's Digest.
Vicuna LLM is an omnibus Large Language Model used in AI research. [1] Its methodology is to enable the public at large to contrast and compare the accuracy of LLMs "in the wild" (an example of citizen science ) and to vote on their output; a question-and-answer chat format is used.