LLM 튜토리얼

Fine-tuning the world's first open-source reasoning model on the medical chain of thought dataset to build better AI doctors for the future.

Learn how to create a simplified implementation of the RStar framework using a combination of neural networks, symbolic reasoning, and Monte Carlo Tree Search (MCTS).

Learn how to set up and run the Genesis Physics Engine on Google Colab, overcoming installation challenges and getting started with physics simulations.

Learn about Mistral's Codestral 25.01, including its capabilities, benchmarks, and how to set it up in VS Code for code assistance.

Learn about NVIDIA’s 3D mesh-generating model, LLaMA-Mesh, including its capabilities, limitations, setup instructions, and examples.

Learn how to build an image captioning app using Streamlit for the front end, Llama 3.2 90B for generating captions, and Groq as the API.

Learn how to fine-tune a multimodal model by Meta AI on the Amazon product dataset using the Unsloth framework.

Learn how to build an AI-powered code reviewer assistant using DeepSeek-V3 and Gradio.

Learn how to set up and run vLLM (Virtual Large Language Model) locally using Docker and in the cloud using Google Cloud.

Learn how to optimize your coding workflow using the ChatGPT desktop app, with a focus on its integration with VS Code, the terminal, and Xcode.

Learn how to align large language models with user preferences using OpenAI's preference fine-tuning and direct preference optimization.

Learn how to build a multilingual code explanation app using Llama 3.3, Hugging Face, and Streamlit.