LLM Tutorials

Learn how to implement late chunking with Jina AI to improve context preservation and retrieval accuracy in RAG applications.

Learn what prompt caching is and how to use it with Ollama to optimize LLM interactions, reduce costs, and improve performance in AI apps.

Learn how to implement recursive retrieval in RAG systems using LlamaIndex to improve the accuracy and relevance of retrieved information, especially for large document collections.

Learn how to evaluate your LLM on code generation capabilities with the Hugging Face Evaluate library.

Learn what speculative decoding is, how it works, when to use it, and how to implement it using Gemma2 models.

Learn how to use OpenAI’s gpt-4o-audio-preview model with LangChain to build voice-enabled applications that include audio input, transcription, and generation.

Learn how to build secure, local AI applications that protect your sensitive data using a low/no-code automation framework.

Get step-by-step instructions on how to set up and run Llama 3.2 1B on your Android device using the Torchchat framework.

Learn how to use Runway Act-One through both the web interface and its API, and discover how to combine it with Runway Gen3-Alpha.

Learn to build AI chatbots with Streamlit, LangChain, and Neo4j. This tutorial covers creating UIs for LLM apps, implementing RAG, and deploying to Streamlit Cloud.

Learn how to build real-time AI applications with OpenAI's Realtime API. This tutorial covers WebSockets, Node.js setup, text/audio messaging, function calling, and deploying a React voice assistant demo.

Discover Microsoft's new LLM series and boost your model's accuracy from 65% to 86% by fine-tuning it on the E-commerce classification dataset.