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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. The largest and most capable LLMs are generative pretrained transformers (GPTs).
The term can be differentiated from traditional staff scheduling.Staff scheduling is rooted in time management.Besides the aspects of demand orientation, workforce modeling also incorporates the forecast of the workload and the required staff, the integration of workers into the scheduling process through interactivity, as well as analyzing the entire process.
Workforce management (WFM) is an institutional process that maximizes performance levels and competency for an organization.The process includes all the activities needed to maintain a productive workforce, such as field service management, human resource management, performance and training management, data collection, recruiting, budgeting, forecasting, scheduling and analytics.
Staffing is the process of finding the right worker with appropriate qualifications or experience and recruiting them to fill a job position or role. [1] [2] Through this process, organizations acquire, deploy, and retain a workforce of sufficient quantity and quality to create positive impacts on the organization's effectiveness. [3]
For large organisations employee scheduling can be complex, [citation needed] and optimising this is framed as the nurse scheduling problem in operations Research. [1] Advanced employee scheduling software also provides ways to connect with the staff, ask for their preferences and communicate the schedule to them.
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]
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