How to Use Language Model Libraries (LLMs) for Text Extraction and Annotation Language Model Libraries (LLMs) are powerful tools for text extraction and annotation. They leverage pre-trained language models to perform a wide range of natural language processing tasks, such as named entity recognition, part-of-speech tagging, and dependency parsing. In Continue Reading
“language models”
How to use LLMs for text summarization and paraphrasing
In recent years, large language models (LLMs) have revolutionized natural language processing tasks such as text summarization and paraphrasing. LLMs like OpenAI’s GPT-3 have shown impressive performance in generating high-quality summaries and paraphrases that can be used in various applications. In this tutorial, we will explore how to use LLMs Continue Reading
How to use LLMs for text generation and diversification
Language models have come a long way in recent years, and one of the most popular and powerful types of language models is the Large Language Model (LLM). LLMs are capable of generating coherent and contextually relevant text, making them extremely useful for a variety of natural language processing (NLP) Continue Reading
How to use LLMs for speech recognition and synthesis
In recent years, Language Model-based approaches have revolutionized the field of speech recognition and synthesis. Large Language Models (LLMs) have been shown to outperform traditional methods, producing more accurate transcriptions and generating more natural-sounding speech. In this tutorial, we will explore how to use LLMs for both speech recognition and Continue Reading
How to use LLMs for text generation and completion
Language Models (LMs) have revolutionized natural language processing tasks such as text generation and completion. LMs like GPT-3 (Generative Pre-trained Transformer 3) have achieved remarkable results in generating coherent and contextually accurate text. One of the popular approaches to building LMs is using the concept of Long Short-Term Memory (LSTM) Continue Reading
How to use LLMs for text generation and optimization
Introduction Language Models (LMs) have revolutionized the field of Natural Language Processing (NLP) by enabling machines to understand and generate human-like text. LMs have numerous applications, including machine translation, sentiment analysis, text summarization, and more. In recent years, Large Language Models (LLMs) have gained significant attention due to their ability Continue Reading
How to use LLMs for machine translation and multilingual communication
How to Use Language Model Multitask Systems (LLMs) for Machine Translation and Multilingual Communication Language Model Multitask Systems (LLMs) have gained significant attention in the field of Natural Language Processing (NLP) for tasks such as machine translation and multilingual communication. LLMs are capable of processing and generating text in multiple Continue Reading
How to use LLMs for chatbot development and conversational AI
How to Use Language Model Modules (LLMs) for Chatbot Development and Conversational AI In recent years, chatbots and conversational AI have gained immense popularity and usage across various industries. Organizations have realized the potential of chatbots in automating customer support, improving user experiences, and increasing engagement. One of the crucial Continue Reading
How to use LLMs for text segmentation and tagging
How to Use Language Model-Based Methods (LLMs) for Text Segmentation and Tagging In this tutorial, we will explore how to use Language Model-Based Methods (LLMs) for text segmentation and tagging. LLMs are powerful models that can generate coherent and structured text representations, allowing for a range of natural language processing Continue Reading
How to use LLMs for natural language inference and reasoning
How to Use Language Model Logics (LLMs) for Natural Language Inference and Reasoning Introduction Natural Language Inference (NLI) and reasoning tasks are crucial for many natural language processing applications, such as question answering, information retrieval, and dialogue systems. However, traditional methods often struggle to accurately understand and reason about the Continue Reading