Recent Advances in Computer Vision and their Business Applications
Introduction: Not long ago, the idea of computers recognizing people, objects, or entire environments seemed futuristic—something you’d expect in sci-fi movies rather than boardrooms or factory floors. Yet today, computer vision has slipped into our everyday lives almost unnoticed. From unlocking smartphones with a glance to self-checkout systems that let shoppers walk out of a…
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Priyadharshini
Unlocking the Power of Sentence Transformers and Text Embeddings in LLMs
Introduction: Large Language Models (LLMs) have dramatically transformed the field of natural language processing (NLP). At the heart of their effectiveness lies one powerful concept: text embeddings. These text embeddings—dense vector representations of language—enable machines to understand, compare, and generate human-like text with remarkable precision. One of the most reliable tools for generating high-quality text…
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Priyadharshini
Fine-Tuning LLMs with LoRA Adapters: A Comprehensive Guide
Introduction Fine-tuning large language models (LLMs) can be computationally expensive and resource-intensive. Low-Rank Adaptation (LoRA) provides a more efficient and affordable way to fine-tune these models. In this blog, we’ll explore what Low-Rank Adaptation (LoRA) is, how it works, and how to apply it for fine-tuning an LLM. What is LoRA? Low-Rank Adaptation (LoRA) is…
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