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The ReAct pattern, a portmanteau of "Reason + Act", constructs an agent out of an LLM, using the LLM as a planner. The LLM is prompted to "think out loud". The LLM is prompted to "think out loud". Specifically, the language model is prompted with a textual description of the environment, a goal, a list of possible actions, and a record of the ...
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024.
OpenAI claims that Codex can create code in over a dozen programming languages, including Go, JavaScript, Perl, PHP, Ruby, Shell, Swift, and TypeScript, though it is most effective in Python. [1] According to VentureBeat, demonstrations uploaded by OpenAI showed impressive coreference resolution capabilities.
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
When assessing the quality of a vector model, a user may draw on this accuracy test which is implemented in word2vec, [28] or develop their own test set which is meaningful to the corpora which make up the model. This approach offers a more challenging test than simply arguing that the words most similar to a given test word are intuitively ...
llama.cpp began development in March 2023 by Georgi Gerganov as an implementation of the Llama inference code in pure C/C++ with no dependencies. This improved performance on computers without GPU or other dedicated hardware, which was a goal of the project.
spaCy (/ s p eɪ ˈ s iː / spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. [3] [4] The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.