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Later, GLaM [39] demonstrated a language model with 1.2 trillion parameters, each MoE layer using top-2 out of 64 experts. Switch Transformers [21] use top-1 in all MoE layers. The NLLB-200 by Meta AI is a machine translation model for 200 languages. [40] Each MoE layer uses a hierarchical MoE with two levels.
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.
List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.
modified_identifier_list «As «non_array_type««array_rank_specifier»» (multiple declarator); valid declaration statements are of the form Dim declarator_list, where, for the purpose of semantic analysis, to convert the declarator_list to a list of only single declarators:
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).
Some languages define a special character as a terminator while some, called line-oriented, rely on the newline. Typically, a line-oriented language includes a line continuation feature whereas other languages have no need for line continuation since newline is treated like other whitespace. Some line-oriented languages provide a separator for ...
The language was inspired by the S programming language, with most S programs able to run unaltered in R. [6] The language was also inspired by Scheme's lexical scoping, allowing for local variables. [1] The name of the language, R, comes from being both an S language successor as well as the shared first letter of the authors, Ross and Robert ...
Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...