Introduction AI is incredible. It can help you write emails, explain complex ideas, brainstorm, and even code. But sometimes, it gets things completely wrong — and says it like it’s 100% right. This strange behavior is known as an AI hallucination: when an AI gives an answer that sounds correct...
Introduction Retrieval-Augmented Generation (RAG) is an advanced technique in natural language processing that enhances language models by enabling them to retrieve external information in real time. This leads to more accurate and context-aware responses, making RAG ideal for tasks that require up-to-date or domain-specific knowledge, such as customer support, enterprise...
Introduction The Hugging Face Inference API makes it easy to send prompts to large language models (LLMs) hosted on the Hugging Face Hub. By combining this with Gradio, you can quickly build interactive chatbots and demos with a simple, web-based user interface—without worrying about backend frameworks. In this tutorial,...
Introduction The Hugging Face Inference API makes it easy to send prompts to large language models (LLMs) hosted on the Hugging Face Hub. By combining this with FastAPI—a modern Python web framework—you can build scalable, production-ready APIs that serve LLM-powered responses to your applications. In this tutorial, you’...
Introduction The Hugging Face Inference API is a powerful service that lets you interact with large language models (LLMs) hosted on the Hugging Face Hub. Whether you’re building chatbots, summarization tools, or other AI-powered applications, the Inference API makes it simple to send prompts to an LLM and receive...
Introduction In today's data-driven world, understanding text data is crucial across various domains, from data analysis to engineering and architecture. However, dealing with text data often requires converting it into numerical representations for machine learning models to process efficiently. This is where embedding vectors come into play, offering...
Introduction In this tutorial, we want to explain why Generative AI (GenAI) is possible now. In order to do this, we describe the key factors that are responsible for the rise of Generative AI. Factors The key factors that enable Generative AI are availability of large datasets, computational power, and...
Introduction In this tutorial, we want to explain how Generative Adversarial Neural Networks (GANs) work. In order to do this, we take a look at the functionality and the idea behind GANs. Principle Generative Adversarial Neural Networks (GANs) are a special type of Artificial Neural Networks. This kind of model...
Introduction In this tutorial, we want to explain Generative AI (GenAI). In order to do this, we describe both the terms Artificial Intelligence, Machine Learning, Deep Learning and Generative AI as well as the relationships between them. Overview First, we want to have a look to the relationships between Artificial...