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[2307.06435] A Comprehensive Overview of Large Language Models - arXiv.org
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction.
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Large language models (LLMs): survey, technical frameworks, and future ...
Large language models (LLMs) like GPT-4, BARD, PaLM, Megatron-Turing NLG, Jurassic-1 Jumbo etc., have contributed to our understanding and application of AI in these domains, along with natural language processing (NLP) techniques.
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A jargon-free explanation of how AI large language models work
Want to really understand large language models? Here’s a gentle primer.
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What is a large language model (LLM)? - Cloudflare
A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks. LLMs are trained on huge sets of data — hence the name"large." LLMs are built on machine learning: specifically, a type of neural network called a transformer model.
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How Large Language Models work - Medium
Thanks to Large Language Models (LLMs) like ChatGPT, Artificial Intelligence has now caught the attention of pretty much everyone, but how these models work is still less widely understood.
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What Are Large Language Models (LLMs)? | IBM
Large language models are AI systems capable of understanding and generating human language by processing vast amounts of text data.
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A Review on Large Language Models: Architectures, Applications ...
Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question answering, etc.
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What is an LLM? A Guide on Large Language Models and How ... - DataCamp
What is a Large Language Model? LLMs are AI systems used to model and process human language. They are called “large” because these types of models are normally made of hundreds of millions or even billions of parameters that define the model's behavior, which are pre-trained using a massive corpus of text data.
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Larger and more instructable language models become less reliable
The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational...
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