How to use LLMs for text generation and evaluation

Language Models, also known as LMs, are a fundamental tool in Natural Language Processing (NLP) tasks such as text generation, machine translation, and speech recognition. Recently, there has been a lot of excitement around Large Language Models (LLMs) due to their ability to generate coherent and contextually relevant text. In 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

How to use LLMs for text correction and editing

How to Use Language Model Libraries (LLMs) for Text Correction and Editing Introduction Language Model Libraries (LLMs) are powerful tools that can be used to correct and edit text. They use natural language processing techniques to analyze and understand text, and then provide suggestions and corrections to improve its quality. Continue Reading

How to use LLMs for data analysis and visualization

LLMs (Language Model Microservices) are powerful tools that allow you to extract insights from text data and visualize them in a meaningful way. In this tutorial, we will explore how to use LLMs for data analysis and visualization. We will cover the following topics: What are LLMs? Setting up LLMs Continue Reading

How to use LLMs for text simplification and readability enhancement

Introduction In today’s digital era, generating simplified and easily understandable text has become increasingly important. Text simplification techniques are used to transform complex and verbose text into simpler and more straightforward language. These techniques are widely employed in various applications, such as educational materials, language translation, and accessibility enhancements for Continue Reading

How to use LLMs for text generation and verification

In the field of natural language processing (NLP), large language models (LLMs) have gained significant attention and popularity over the past few years. These models, often based on deep learning techniques, are able to generate high-quality text that is virtually indistinguishable from human-written content. LLMs can also be used for Continue Reading

How to use LLMs for semantic parsing and knowledge graph construction

How to Use Language Model to Construct Knowledge Graphs and Perform Semantic Parsing In this tutorial, we will explore how to use Language Models (LMs) for semantic parsing and knowledge graph construction. Semantic parsing is the process of converting natural language into a structured representation that can be understood by Continue Reading