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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. This page lists notable large language models.
As of 2024, some of the most powerful language models, such as o1, Gemini and Claude 3, were reported to achieve scores around 90%. [ 4 ] [ 5 ] An expert review of 5,700 of the questions, spanning all 57 MMLU subjects, estimated that there were errors with 6.5% of the questions in the MMLU question set, which suggests that the maximum ...
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).
Goldman Sachs analyst Ronald Keung maintained a Buy on Alibaba Group Holdings (NYSE:BABA) with a price target of $117. Keung noted Alibaba’s Qwen2.5 family continues to gain traction in ...
Multiple publications viewed this as a response to Meta and others open-sourcing their AI models, and a stark reversal from Google's longstanding practice of keeping its AI proprietary. [35] [36] [37] Google announced an additional model, Gemini 1.5 Flash, on May 14th at the 2024 I/O keynote. [38] Gemma 2 was released on June 27, 2024. [39]
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.
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. [4] Llama models are trained at different parameter sizes, ranging between 1B and 405B. [5]
In April 2023, Huawei released a paper detailing the development of PanGu-Σ, a colossal language model featuring 1.085 trillion parameters. Developed within Huawei's MindSpore 5 framework, PanGu-Σ underwent training for over 100 days on a cluster system equipped with 512 Ascend 910 AI accelerator chips, processing 329 billion tokens in more than 40 natural and programming languages.