Category: blogathon
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A Complete Guide to Using Cohere AI
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Introduction This guide primarily introduces the readers to Cohere, an Enterprise AI platform for search, discovery, and advanced retrieval. Leveraging state-of-the-art Machine Learning techniques enables organizations to extract valuable insights, automate tasks, and enhance customer experiences through advanced understanding. Cohere empowers businesses and individuals across industries to unlock the full potential of their textual data,…
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A Beginner’s Guide to Evaluating RAG Pipelines Using RAGAS
Introduction In the ever-evolving landscape of machine learning and artificial intelligence, the development of language model applications, particularly Retrieval Augmented Generation (RAG) systems, is becoming increasingly sophisticated. However, the real challenge surfaces not during the initial creation but in the ongoing maintenance and enhancement of these applications. This is where RAGAS—an evaluation library dedicated to…
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Advanced RAG Technique : Langchain ReAct and Cohere
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in API, blogathon, framework, Generative AI, Guide, Intermediate, langchaian, Langchain, Large Language Models, LLM, LLMs, Models, Python, query, strategy, vectorIntroduction This article explores Adaptive Question-Answering (QA) frameworks, specifically the Adaptive RAG strategy. It discusses how this framework dynamically selects the most suitable method for large language models (LLMs) based on query complexity. It highlights the learning objectives, features, and implementation of Adaptive RAG, its efficiency, and its integration with Langchain and Cohere LLM. The…
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Understanding Fuzzy C Means Clustering
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Introduction Clustering is an unsupervised machine learning algorithm that groups together similar data points based on criteria like shared attributes. Each cluster has data points that are similar to the other data points in the cluster while as a whole, the cluster is dissimilar to other data points. By making use of clustering algorithms, we…
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Finetuning Llama 3 with Odds Ratio Preference Optimization
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Introduction Large Language Models are often trained rather than built, requiring multiple steps to perform well. These steps, including Supervised Fine Tuning (SFT) and Preference Alignment, are crucial for learning new things and aligning with human responses. However, each step takes a significant amount of time and computing resources. One solution is the Odd Ratio…
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Phi 3 – Small Yet Powerful Models from Microsoft
Introduction The Phi model from Microsoft has been at the forefront of many open-source Large Language Models. Phi architecture has led to all the popular small open-source models that we see today which include TPhixtral, Phi-DPO, and others. Their Phi Family has taken the LLM architecture a step forward with the introduction of Small Language…
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GhostFaceNets: Efficient Face Recognition on Edge Devices
Introduction GhostFaceNets is a revolutionary facial recognition technology that uses affordable operations without compromising accuracy. Inspired by attention-based models, it revolutionizes facial recognition technology. This blog post explores GhostFaceNets through captivating visuals and insightful illustrations, aiming to educate, motivate, and spark creativity. The journey is not just a blog post, but a unique exploration of…
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Implementing Query2Model: Simplifying Machine Learning
Introduction Embark on an exciting journey into the world of effortless machine learning with “Query2Model”! This innovative blog introduces a user-friendly interface where complex tasks are simplified into plain language queries. Explore the fusion of natural language processing and advanced AI models, transforming intricate tasks into straightforward conversations. Join us as we delve into the…