A new preprint details a practical guide to the modern Natural Language Processing (NLP) pipeline, covering everything from tokenization to reinforcement learning from human feedback. The guide is structured as a reproducible research artifact with twelve hands-on sessions, emphasizing open-weight models and the Hugging Face ecosystem. It includes original research on adapting NLP techniques for low-resource languages like Tajik and Tatar. AI
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IMPACT Provides a hands-on guide for implementing and comparing NLP methods, from classical ML to LLM-based systems.
RANK_REASON This is a research paper detailing a practical guide to NLP techniques.