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  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    [4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.

  3. Vicuna LLM - Wikipedia

    en.wikipedia.org/wiki/Vicuna_LLM

    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.

  4. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    Here are two simple text documents: (1) John likes to watch movies. ... Python implementation ... In practice, hashing simplifies the implementation of bag-of-words ...

  5. Llama (language model) - Wikipedia

    en.wikipedia.org/wiki/Llama_(language_model)

    Two separate reward models were trained from these preferences for safety and helpfulness using Reinforcement learning from human feedback (RLHF). A major technical contribution is the departure from the exclusive use of Proximal Policy Optimization (PPO) for RLHF – a new technique based on Rejection sampling was used, followed by PPO.

  6. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    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.

  7. MMLU - Wikipedia

    en.wikipedia.org/wiki/MMLU

    The MMLU consists of about 16,000 multiple-choice questions spanning 57 academic subjects including mathematics, philosophy, law, and medicine. It is one of the most commonly used benchmarks for comparing the capabilities of large language models, with over 100 million downloads as of July 2024. [1] [2]

  8. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    Ensemble learning, including both regression and classification tasks, can be explained using a geometric framework. [15] Within this framework, the output of each individual classifier or regressor for the entire dataset can be viewed as a point in a multi-dimensional space.

  9. ROUGE (metric) - Wikipedia

    en.wikipedia.org/wiki/ROUGE_(metric)

    The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced) summary or translation. ROUGE metrics range between 0 and 1, with higher scores indicating higher similarity between the automatically produced summary and the reference.