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This repository includes a variety of notebooks designed for tasks ranging from generative ai text models to image generation and model training to data analysis and visualization.
A collection of practical examples and tutorials for fine-tuning large language models using Factory. Includes Docker images, Jupyter notebooks, and utility scripts for easy model training and deployment.
A hands-on collection of practical notebooks for learning and building with LLMs , including prompt engineering, RAG, fine-tuning, and evaluation. Built for aspiring AI engineers using only free and open-source tools.
An LLM-powered augmented generation suite leveraging LangChain, Ollama, and vector databases to enhance response quality through caching, contextual memory, and retrieval-based methods. This collection of Jupyter notebooks showcases modular techniques for building intelligent, memory-efficient generative systems with real-time semantic awareness.