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An Introduction to Large Language Models (LLMs)

Analytics Vidhya

Introduction Large Language Models (LLMs) are foundational machine learning models that use deep learning algorithms to process and understand natural language. These models are trained on massive amounts of text data to learn patterns and entity relationships in the language.

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Exploring the Use of LLMs and BERT for Language Tasks

Analytics Vidhya

Introduction In the rapidly evolving landscape of artificial intelligence, especially in NLP, large language models (LLMs) have swiftly transformed interactions with technology. This article explores […] The post Exploring the Use of LLMs and BERT for Language Tasks appeared first on Analytics Vidhya.

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Beyond Words: Unleashing the Power of Large Language Models

Analytics Vidhya

Introduction In the realm of artificial intelligence, a transformative force has emerged, capturing the imaginations of researchers, developers, and enthusiasts alike: large language models.

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Beginners’ Guide to Finetuning Large Language Models (LLMs)

Analytics Vidhya

The seismic impact of finetuning large language models has utterly transformed NLP, revolutionizing our technological interactions. Rewind to 2017, a pivotal moment marked by […] The post Beginners’ Guide to Finetuning Large Language Models (LLMs) appeared first on Analytics Vidhya.

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Supercharging Graph Neural Networks with Large Language Models: The Ultimate Guide

Unite.AI

In parallel, Large Language Models (LLMs) like GPT-4, and LLaMA have taken the world by storm with their incredible natural language understanding and generation capabilities. In this article, we will delve into the latest research at the intersection of graph machine learning and large language models.

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Building Language Models: A Step-by-Step BERT Implementation Guide

Analytics Vidhya

A great example is the announcement that BERT models are now a significant force behind Google Search. Google believes that this move […] The post Building Language Models: A Step-by-Step BERT Implementation Guide appeared first on Analytics Vidhya.

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LogLLM: Leveraging Large Language Models for Enhanced Log-Based Anomaly Detection

Marktechpost

Traditional techniques include reconstruction-based methods (such as autoencoders and GANs), which rely on training models to reconstruct normal log sequences and detect anomalies based on reconstruction errors. It leverages BERT to extract semantic vectors and uses Llama, a transformer decoder, for log sequence classification.