Category: Guide
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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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RAG Application with Cohere Command-R and Rerank – Part 1
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Introduction The Retrieval-Augmented Generation approach combines LLMs with a retrieval system to improve response quality. However, inaccurate retrieval can lead to sub-optimal responses. Cohere’s re-ranker model enhances this process by evaluating and ordering search results based on contextual relevance, improving accuracy and saving time for specific information seekers. This article provides a guide on implementing…
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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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Nvidia Introduces VILA: Visual Language Intelligence and Edge AI 2.0
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in AI, Applications, Artificial Intelligence, Edge AI 2.0, Guide, images, Intermediate, IOT, language models, LLM, LLMs, Models, NVIDIA, training, VILA, visual modelIntroduction Visual Language Models (VLMs) are revolutionizing the way machines comprehend and interact with both images and text. These models skillfully combine techniques from image processing with the subtleties of language comprehension. This integration enhances the capabilities of artificial intelligence (AI). Nvidia and MIT have recently launched a VLM named VILA, enhancing the capabilities of…
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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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How to Use Llama 3 as Copilot in VS Code for Free
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Introduction You’ve probably heard all the hype around Meta‘s latest release, Llama 3. This sophisticated AI model has been integrated into various platforms to enhance their capabilities and expand industry applications. Did you know that it can even help to improve the coding process in Visual Studio Code (VS Code)? Yes, in fact, Llama 3…
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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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Building Responsible AI with Guardrails AI
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in AI, API, Applications, ChatGPT, Github, Guide, Intermediate, language models, Large Language Models, LLMs, Models, Object, Python, validationIntroduction Large Language Models (LLMs) are ubiquitous in various applications such as chat applications, voice assistants, travel agents, and call centers. As new LLMs are released, they improve their response generation. However, people are increasingly using ChatGPT and other LLMs, which may provide prompts with personal identifiable information or toxic language. To protect against these…
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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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Build a Winning Dream 11 Team Using Python and AI
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Introduction The exponential rise of IPL in India has correlatively resulted in the growth of fantasy cricket in the country. In recent years, we have seen more and more people playing on platforms like Dream 11, My Circle, etc. every day. Dream11 is a fantasy sports app where you can create your fantasy team for…
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99% of Python Developers Don’t Know These Pandas Tricks!
Introduction While working with Pandas in Python, you may often notice that your code is slow, it uses too much memory, or it gets difficult to handle as your data grows larger. Any of these issues can lead to errors, long wait times for analysis, and limitations in processing bigger datasets. In this article, we…
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RAG and Streamlit Chatbot: Chat with Documents Using LLM
Introduction This article aims to create an AI-powered RAG and Streamlit chatbot that can answer users questions based on custom documents. Users can upload documents, and the chatbot can answer questions by referring to those documents. The interface will be generated using Streamlit, and the chatbot will use open-source Large Language Model (LLM) models, making…
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How Data Efficient GANs Generate Images of Cats and Dogs?
Introduction Generative adversarial networks are a popular framework for Image generation. In this article we’ll train Data-efficient GANs with Adaptive Discriminator Augmentation that addresses the challenge of limited training data. Adaptive Discriminator Augmentation dynamically adjusts data augmentation during GAN training, preventing discriminator overfitting and enhancing model generalization. By employing invertible augmentation techniques and probabilistic application,…
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Flask Application Dockerization: Creating a Docker Image
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Introduction In the fast-paced software development industry, mastering robust application management and smooth deployment is crucial. Docker, a game-changing technology, has revolutionized software distribution, running, and bundles by separating applications from infrastructure, enabling quick software delivery. It improves portability, scalability, and workflow optimization, making it a standard component in current development practices. This article aims…
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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…