Analytics Vidhya

AUGUST 2, 2023

Introduction Over the past few years, the landscape of natural language processing (NLP) has undergone a remarkable transformation, all thanks to the advent of large language models. But […] The post A Comprehensive Guide to Fine-Tuning Large Language Models appeared first on Analytics Vidhya.

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Analytics Vidhya

MAY 6, 2023

Introduction Large Language Models (LLMs) are now widely used in a variety of applications, like machine translation, chat bots, text summarization , sentiment analysis , making advancements in the field of natural language processing (NLP).

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Analytics Vidhya

AUGUST 29, 2023

Introduction Embark on a journey through the evolution of artificial intelligence and the astounding strides made in Natural Language Processing (NLP). The seismic impact of finetuning large language models has utterly transformed NLP, revolutionizing our technological interactions.

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Marktechpost

JULY 14, 2024

Large language models (LLMs) have shown exceptional capabilities in understanding and generating human language, making substantial contributions to applications such as conversational AI. Chatbots powered by LLMs can engage in naturalistic dialogues, providing a wide range of services.

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Unite.AI

JULY 4, 2024

Gemma 2 is Google's newest open-source large language model, designed to be lightweight yet powerful. It's built on the same research and technology used to create Google's Gemini models, offering state-of-the-art performance in a more accessible package. What is Gemma 2?

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Unite.AI

NOVEMBER 14, 2023

The belief that natural language processing by AI can fully replace the precision and complexity of formal mathematical notations and traditional programming is, at best, premature. The post Will Large Language Models End Programming? appeared first on Unite.AI.

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Unite.AI

MARCH 22, 2024

Since OpenAI unveiled ChatGPT in late 2022, the role of foundational large language models (LLMs) has become increasingly prominent in artificial intelligence (AI), particularly in natural language processing (NLP).

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Marktechpost

JULY 25, 2024

Large Language Models (LLMs) have revolutionized AI with their ability to understand and generate human-like text. Learning about LLMs is essential to harness their potential for solving complex language tasks and staying ahead in the evolving AI landscape.

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Flipboard

OCTOBER 18, 2023

Large Language Models (LLMs) have unlocked a new era in natural language processing. Go from learning what large language models are to building and deploying LLM apps in 7 easy steps with this guide. So why not learn more about them?

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Towards AI

AUGUST 6, 2024

Master LLMs & Generative AI Through These Five Books This article reviews five key books that explore the rapidly evolving fields of large language models (LLMs) and generative AI, providing essential insights into these transformative technologies.

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Large Language Models Generative AI Natural Language Processing Prompt Engineer 91

Analytics Vidhya

SEPTEMBER 18, 2024

Introduction Large Language Models (LLMs) contributed to the progress of Natural Language Processing (NLP), but they also raised some important questions about computational efficiency. These models have become too large, so the training and inference cost is no longer within reasonable limits.

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Unite.AI

DECEMBER 14, 2023

Data contamination in Large Language Models (LLMs) is a significant concern that can impact their performance on various tasks. What Are Large Language Models? LLMs have gained significant popularity and are widely used in various applications, including natural language processing and machine translation.

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Towards AI

SEPTEMBER 30, 2024

We are aware that in recent times, large language models (LLMs) have completely changed how we interact with technology, enabling applications in natural language processing, coding, and reasoning. However, one significant challenge remains the ability of these models to self-correct their mistakes.

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Marktechpost

JUNE 10, 2024

The emergence of large language models (LLMs) such as Llama, PaLM, and GPT-4 has revolutionized natural language processing (NLP), significantly advancing text understanding and generation. Sources [link] The post Hallucination in Large Language Models (LLMs) and Its Causes appeared first on MarkTechPost.

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Large Language Models Categorization Data Quality Natural Language Processing 141

Marktechpost

OCTOBER 13, 2024

Mixture of Experts (MoE) models are becoming critical in advancing AI, particularly in natural language processing. MoE architectures differ from traditional dense models by selectively activating subsets of specialized expert networks for each input.

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Marktechpost

MARCH 8, 2024

The relentless advancement in natural language processing (NLP) has ushered in an era of large language models (LLMs) capable of performing various complex tasks with unprecedented accuracy. The innovative handling of weight outliers and optimization of quantization ranges to minimize quantization error.

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Marktechpost

APRIL 25, 2024

Are you curious about the intricate world of large language models (LLMs) and the technical jargon that surrounds them? LLM (Large Language Model) Large Language Models (LLMs) are advanced AI systems trained on extensive text datasets to understand and generate human-like text.

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Analytics Vidhya

SEPTEMBER 15, 2024

Introduction Recently, with the rise of large language models and AI, we have seen innumerable advancements in natural language processing. Models in domains like text, code, and image/video generation have archived human-like reasoning and performance.

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Marktechpost

JULY 26, 2024

Large language models’ (LLMs) training pipelines are the source of inspiration for this method in the field of natural language processing (NLP). Tokenizing input is a crucial part of LLM training, and it’s commonly accomplished using byte pair encoding (BPE).

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Machine Learning Research at Apple

AUGUST 4, 2024

This paper was accepted at the ACL 2024 Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various tasks. However, their substantial computational and memory requirements present challenges, especially for devices with limited DRAM capacity.

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Marktechpost

JULY 22, 2024

Large Language Models (LLMs) have revolutionized natural language processing, demonstrating remarkable capabilities in various applications. Transformer architecture has emerged as a major leap in natural language processing, significantly outperforming earlier recurrent neural networks.

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Unite.AI

DECEMBER 4, 2023

Small Language Models (SLM) are emerging and challenging the prevailing narrative of their larger counterparts. Despite their excellent language abilities these models are expensive due to high energy consumption, considerable memory requirements as well as heavy computational costs.

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Towards AI

AUGUST 10, 2023

Embarking on a Journey with Large Language Models (LLMs) This member-only story is on us. The world of artificial intelligence has been revolutionized by the emergence of Large Language Models (LLMs). Upgrade to access all of Medium. Join thousands of data leaders on the AI newsletter.

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Marktechpost

APRIL 30, 2024

Large Language Models (LLMs) signify a revolutionary leap in numerous application domains, facilitating impressive accomplishments in diverse tasks. With billions of parameters, these models demand extensive computational resources for operation. Yet, their immense size incurs substantial computational expenses.

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Analytics Vidhya

JUNE 13, 2024

Introduction Large language models (LLMs) have revolutionized natural language processing (NLP), enabling various applications, from conversational assistants to content generation and analysis.

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Marktechpost

MAY 27, 2024

Knowledge-intensive Natural Language Processing (NLP) involves tasks requiring deep understanding and manipulation of extensive factual information. These tasks challenge models to effectively access, retrieve, and utilize external knowledge sources, producing accurate and relevant outputs.

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Marktechpost

JULY 7, 2024

Natural language processing (NLP) drives researchers to develop algorithms that enable computers to understand, interpret, and generate human languages. The problem concerns the inefficiencies and limitations of tokenizers used in large language models (LLMs).

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Marktechpost

SEPTEMBER 17, 2024

Prior research on Large Language Models (LLMs) demonstrated significant advancements in fluency and accuracy across various tasks, influencing sectors like healthcare and education. This progress sparked investigations into LLMs’ language understanding capabilities and associated risks.

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Analytics Vidhya

JUNE 6, 2024

Introduction Large Language Models are known for their text-generation capabilities. This will help the large language models understand English text and generate meaningful full tokens during the generation period. They are trained with millions of tokens during the pre-training period.

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Marktechpost

OCTOBER 2, 2024

Large Language Models (LLMs) have made significant strides in various Natural Language Processing tasks, yet they still struggle with mathematics and complex logical reasoning. However, LLMs often exhibit unfaithful reasoning, where conclusions don’t align with the generated reasoning chain.

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SAS Software

JULY 9, 2024

The post Natural Language Processing techniques that improve data quality with LLMs appeared first on SAS Blogs.

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Marktechpost

DECEMBER 4, 2023

Large Language Models (LLMs) are artificial intelligence models for natural language processing tasks. These models are trained on massive datasets and can understand and generate human-like text. The researchers are working to improve the model’s performance and solve the limitations.

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Marktechpost

MAY 2, 2024

The development of natural language processing has been significantly propelled by the advancements in large language models (LLMs). This innovative framework significantly reduces latency, making it highly suitable for real-time natural language processing applications. With up to a 1.7×

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SAS Software

MARCH 11, 2024

While large language models (LLMs) have become synonymous with advanced AI capabilities, their integration into various business and technological domains is often accompanied by significant costs. These costs arise from the extensive computational resources required for training and running these models.

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Marktechpost

SEPTEMBER 20, 2024

Multimodal large language models (MLLMs) focus on creating artificial intelligence (AI) systems that can interpret textual and visual data seamlessly. The NVLM-H model, in particular, strikes a balance between image processing efficiency and multimodal reasoning accuracy, making it one of the most promising models in this field.

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Marktechpost

AUGUST 31, 2024

Large Language Models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. However, they face a significant challenge: hallucinations, where the models generate responses that are not grounded in the source material.

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Analytics Vidhya

AUGUST 1, 2024

Introduction Mistral NeMo is a pioneering open-source large language model developed by Mistral AI in collaboration with NVIDIA, designed to deliver state-of-the-art natural language processing capabilities. This model, boasting 12 billion parameters, offers a large context window of up to 128k tokens.

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