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Bookmark or Share- What are Large Language Models? | A Comprehensive LLMs GuideA 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.
- Understanding LLMs: A Comprehensive Overview from Training to InferenceIn this section, we will provide an overview of the model training techniques. This will include an introduction to the relevant training datasets, data preparation and preprocessing, model architecture, specific training methodologies, model evaluation, and commonly used training frameworks for LLMs.
- Introduction to Large Language Models - Google DevelopersDefine language models and large language models (LLMs). Define key LLM concepts, including Transformers and self-attention. Describe the costs and benefits of LLMs, along with common use...
- Large language model - WikipediaThe largest and most capable LLMs are artificial neural networks built with a decoder-only transformer-based architecture, enabling efficient processing and generation of large-scale text data.
- A jargon-free explanation of how AI large language models workA key innovation of LLMs is that they don’t need explicitly labeled data. Instead, they learn by trying to predict the next word in ordinary passages of text.
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