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5 articles
Fine-tune language models on your domain's data using parameter-efficient techniques like LoRA and QLoRA, with practical guidance on dataset preparation, training strategies, and evaluation methods that produce useful specialists without massive compute budgets.
A practical guide to fine-tuning language models on domain-specific data, covering dataset preparation, training strategies, evaluation methods, and deployment considerations for production systems.
How to build production-ready NLP pipelines — covering text preprocessing, tokenization, embeddings, classification, and entity extraction with practical TypeScript and Python examples.
A developer-friendly walkthrough of the Transformer architecture that powers GPT, BERT, and modern LLMs — covering self-attention, positional encoding, and the encoder-decoder structure with code examples.
A practical introduction to natural language processing concepts web developers need — tokenization, sentiment analysis, named entity recognition, and integrating NLP APIs into applications.