
Fine-Tuning Language Models on Domain-Specific Data
Fine-tune language models on your domain with parameter-efficient LoRA and QLoRA: dataset preparation, training strategies and evaluation, on a small budget.
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5 articles

Fine-tune language models on your domain with parameter-efficient LoRA and QLoRA: dataset preparation, training strategies and evaluation, on a small budget.

A practical guide to fine-tuning language models on domain data: dataset preparation, training strategies, evaluation and production deployment.

How to build production-ready NLP pipelines: text preprocessing, tokenization, embeddings, classification and entity extraction in TypeScript and Python.

A developer-friendly walkthrough of the Transformer architecture behind GPT, BERT and modern LLMs: self-attention, positional encoding, encoder-decoder.

A practical introduction to the NLP concepts web developers need: tokenization, sentiment analysis, named entity recognition and integrating NLP APIs.