What is LLM (Large Language Model) | Large Language Models (LLMs) Explained | LLM Models in AI скачать в хорошем качестве

What is LLM (Large Language Model) | Large Language Models (LLMs) Explained | LLM Models in AI

#llm #largelanguagemodels #ai Large language models, also known as LLMs, are very large deep learning models that are pre-trained on vast amounts of data. The underlying transformer is a set of neural networks that consist of an encoder and a decoder with self-attention capabilities. The encoder and decoder extract meanings from a sequence of text and understand the relationships between words and phrases in it. Transformer LLMs are capable of unsupervised training, although a more precise explanation is that transformers perform self-learning. It is through this process that transformers learn to understand basic grammar, languages, and knowledge. Unlike earlier recurrent neural networks (RNN) that sequentially process inputs, transformers process entire sequences in parallel. This allows the data scientists to use GPUs for training transformer-based LLMs, significantly reducing the training time. What are applications of large language models? There are many practical applications for LLMs. Copywriting Apart from GPT-3 and ChatGPT, Claude, Llama 2, Cohere Command, and Jurassiccan write original copy. AI21 Wordspice suggests changes to original sentences to improve style and voice. Knowledge base answering Often referred to as knowledge-intensive natural language processing (KI-NLP), the technique refers to LLMs that can answer specific questions from information help in digital archives. An example is the ability of AI21 Studio playground to answer general knowledge questions. Text classification Using clustering, LLMs can classify text with similar meanings or sentiments. Uses include measuring customer sentiment, determining the relationship between texts, and document search. Code generation LLM are proficient in code generation from natural language prompts. Examples include Amazon CodeWhisperer and Open AI's codex used in GitHub Copilot, which can code in Python, JavaScript, Ruby and several other programming languages. Other coding applications include creating SQL queries, writing shell commands and website design. Learn more about AI code generation. Text generation Similar to code generation, text generation can complete incomplete sentences, write product documentation or, like Alexa Create, write a short children's story.