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NLP (Natural Language Processing) is a field of AI focused on understanding and processing human language. LLMs, on the other hand, are specific models used within NLP that excel at language-related tasks, thanks to their large size and ability to generate text.
A. Evaluating LLM performance involves appraising factors like language fluency, coherence, contextual understanding, factual accuracy, and the ability to generate relevant and meaningful responses. Metrics such as perplexity, BLEU score, and human evaluations can measure and compare LLM performance.
How can Large Language Models be used? Completion: Given a partial sentence, it can predict the next words. Question answering: You ask a question, and it generates a relevant answer. Translation, summarization, and more: The model can be adapted for various text generation tasks.
NLP (Natural Language Processing) is a field of AI focused on understanding and processing human language. LLMs, on the other hand, are specific models used within NLP that excel at language-related tasks, thanks to their large size and ability to generate text.
A large language model (LLM) is a deep learning algorithm that can perform a variety of natural language processing (NLP) tasks. Large language models use transformer models and are trained using massive datasets ? hence, large. This enables them to recognize, translate, predict, or generate text or other content.