#transformers

'A practical walkthrough to run a GPT-style conversational agent locally using Hugging Face Transformers, complete with code, prompt patterns, and a demo.'

'A practical tutorial showing how to build a local AI agent that thinks, plans, and controls a simulated desktop with step-by-step Python code and examples.'

'An accessible explainer of how modern AI systems combine latent diffusion and transformers to generate realistic video clips, why the outputs vary, and what the costs and benefits are.'

This tutorial shows how to create a compact AI agent that integrates multiple NLP tools using Hugging Face models, enabling tasks like chat, sentiment analysis, and calculations in one package.

Microsoft researchers demonstrate that the Muon optimizer drastically speeds up grokking in Transformer models, enabling faster transition from memorization to generalization compared to AdamW.